[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User]
По материалам СБУ впервые в Украине вынесен приговор митрополиту УПЦ (МП): он признал, что виновен в преступлениях, — пресслужба СБУ
По материалам СБУ районный суд г. Кропивницкий впервые в Украине вынес приговор высокопоставленному клирику УПЦ (МП), экс-руководителю Кировоградской епархии митрополиту Иосафу. Он и секретарь этого учреждения полностью признали свою вину в преступлениях, которые им инкриминировала Служба безопасности. Таким образом, суд и сами фигуранты полностью подтвердили доказательную базу, собранную сотрудниками СБУ.
Фигуранты публично восхваляли захват части территории Украины и "раздували" межрелигиозную вражду в регионе в пользу страны-агрессора. По данным расследования, епископ входил в ближайшее окружение московского патриарха Кирилла, с которым координировал подрывную деятельность против нашего государства.
Агент Украины


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User]
Київський райсуд Харкова скасував штраф
Терехову
 за ведення соцмереж російською і ухвалив, що Кремінь - довбойоб.


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User]
Основные заявления Дениса Пушилина:
⏺
ВСУ попытались прорвать линию обороны в ДНР, используя большое количество техники. Наши войска были к этому готовы и успешно отразили атаку.
⏺
Киев не считается с военными потерями и будет продолжать предпринимать попытки наступления.
⏺
Противника необходимо отодвинуть, как минимум, на 500 км от границ новых субъектов.
⏺
После восстановления Артемовска является возможным вариант с проведением референдума о названии города.
⏺
Республика может помочь Херсонской области в ликвидации последствий разрушения Каховской ГЭС.
⏺
Украина пошла на разрушение гидроэлектростанции, чтобы не допустить российского наступления.


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User] Підари в ході наступальних дій зайняли східну частину населеного пункта Іванівське, бахмутський напрямок і продовжують розвивати успіх у селищі.


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User]
Теперь я понимаю, что ждёт города?!
Антон, вечер добрый!
Начинается веселье. В городе Калуш Ивано-Франковской обл. хотят отключить свет на очистных, как следствие всё и вся останется без воды и туалета..... в место того, что бы заплатить за электричество они будут ставить био.туалеты и платить за них 1.5 миллиона в день.


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User]
🚷
 Ще 490 окупантів знищили Сили оборони України! 126650 осіб – орієнтовні втрати російських загарбників
🇺🇦
 Ракетні війська та артилерія уразили три пункти управління, чотири райони зосередження та два склади боєприпасів окупантів.
💥
✈
 Українська авіація завдала 4 удари по районах зосередження ворога.
🔥
🎞
 Більше – у хроніці 341 доби великої визвольної війни.
Наша боротьба за свободу триває!
🇺🇦


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User]
🤯

Одиночный ПРОТЕСТ против готовки еды.
Кто-то сегодня останется без рождественского ужина.
ТРУХА
⚡
Одесса
 |
Прислать новость


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User]
«Они хотят убежать», - заявил Подоляк, отвечая на вопрос открытия границ.
«Не надо спекуляций. Что значит ограничение прав?
Кроме прав людей в Украине есть обязанность какая-то или нет? Или мы только о правах?
Что государство должно обеспечить чем-то, дать возможность выехать, дать возможность жить, как человек хочет.
Да, в мирное время все дадим. Но во время войны так не ставится вопрос. Хочешь пересечь границу?
То есть хочешь сказать, что Украина должна перестать существовать, потому что ты пересек границу. Потому что когда мы говорим «открыть границы для мужчин», это означает – кто хочет убежать от принятия мужского решения, а они хотят убежать»
Видишь, как много тебе давало государство - право жить, как ты хочешь. Не замечал? А так оно и было.
А теперь ты, собака, убежать хочешь? Нет уж, будь добр на фронт.  Убежать могут только друзья Зеленского и дети призывного возраста Данилова и Ко.
А ты отрабатывай право жить.


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User]
Пам’ятний день для українців.
Вісім років тому в ці дні наші мужні воїни вкотре показали ворогу свою міць і незламність у боях за Дебальцеве.
Утримуючи Дебальцевський виступ, українські захисники сковували переважаючі сили противника та зірвали плани бойовиків на масштабний наступ.
Слава нашим героям!
Вічна пам'ять воїнам, які звідти повернулись на щиті...
Їхні імена назавжди вписані в історію нашої держави, в історію нашої остаточної перемоги над російськими окупантами.
За нами правда!
За нами перемога!
🇺🇦
t.me/cherkaskaODA


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User]
Русские "сюрпризы" под Авдеевкой шокировали украинцев. И это только начало
С каждым днем положение украинских войск на фронте ухудшается,
пишет
 Fakt. Теперь им приходится ожидать ударов не только с воздуха, но и из-под земли.
"Русские копают туннели ближе к нашим позициям, во-первых, для маскировки, а во-вторых, чтобы неожиданно выйти к нашим линиям обороны", — утверждает украинский военный Антон Коцукон.
И это только начало неприятностей. Как прогнозирует польский генерал Вальдемар Скшипчак, Россия готовит Украине кое-что похуже. Планируются масштабные наступления этой зимой, а военные части пополнятся новоприбывшими россиянами, которые до настоящего времени проходили подготовку, считает он.


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User]
Ваня, визнай, що ти вдарив у штангу і всі копіпастери написали те, в чому ти сам був не впевнений.
Таке інколи буває, всі ми помиляємося, не зазнавайся!
UPD: щодо ранкового звіту, про який ми з тобою говорили, все-таки то був Шахед тоді
😂

UPD2: не розганяйте зраду, все 4.5.0
@operatyvnii


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User]
⚡
27 ноября не будет света в Чугуеве
По сообщению энергетиков, 27 ноября, в связи с ремонтными работами, отключат электроэнергию в городе Чугуев по следующим адресам:
▪
9.00-17.00: ул. Литвиновая, ул. Манежно, ул. Староникольская, 50-54;
▪
14.00-16.00: ул. Верхняя Успенская (бывшая Горького), ул. Купальный спуск, ул. Речная, ул. Якова Остряницы, ул. Гвардейская, 5-26, ул. Литвиновая, ул. Манежно, ул. Староникольская, 50-64.


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User]
🏥
Разом з Уповноваженим Президента України з питань реабілітації учасників бойових дій Вадимом Свириденком з робочим візитом відвідав Чернівецький обласний госпіталь ветеранів війни.
Зокрема, ознайомилися з роботою закладу в умовах війни та обговорили з працівниками його нагальні потреби.
💊
Здоров’я та реабілітація наших захисників – це пріоритет №1. Маємо подбати, аби їхнє відновлення проходило ефективно й було на найвищому рівні.
📍
Для того, аби надавати якісні реабілітаційні послуги, госпіталю потрібно придбати певне медичне обладнання та провести навчання для персоналу.


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User] Байден во время своей ответной речи Путину заявил, что "НАТО сохранило свое единство как никогда ранее". Из его уст бы да мед пить. Никто в НАТО нас непосредственно защищать не собирается, даже англичане и поляки. Все нами только пользуются в своих корыстных целях. Где он это единство увидел? Из-за танков даже перегрызлись. А глава МИД Словакии Качер даже обматерил премьер-министра Венгрии Орбана из-за его позиции по Украине и желания соблюсти свои национальные интересы, в то время как той же Словакии партнеры по НАТО "выкручивают руки", чтобы максимально выжать из страны все что только можно, чтобы отправить в Украину.


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User]
«Тихо зайшли, тихо відійшли» – це гасло спеціалістів інженерно-саперної справи. Від їхньої роботи залежить просування ворожих сил на конкретних ділянках і не можливість пройти вперед. При зупинці техніки, деморалізована піхота фактично стає.
«Мінуємо шляхи підходу противника до наших позицій. Проходи як для техніки так і піхоти, які хочуть дійти до наших країв. На тій ділянці, де робимо це ми, нещодавно вже 4 одиниці ворожої техніки зупинили – два танки і дві БМП чи МТ-ЛБ» - розповідає Олександр «Техас», головний сержант інженерно-саперної роти 46 окрема аеромобільна бригада ДШВ ЗС України
Підрозділ Олександра мінує все, куди може пройти ворог – дороги, поля.
«Все закривається так, що проходу не буде. Ну і готуємо для ворога сюрприз. Воно ще не використане, - сміється «Техас».
 Хочеться, щоб усе якнайшвидше закінчилося і додому. А поки – гнатимемо ворога. Хлопці, які зі мною поруч – найкращі люди цієї країни»
Служба зв’язків з громадськістю Командування Десантно-штурмових військ Збройних Сил України


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User]
«Кто научит своих не бросать?»
  — песня о наших защитниках от инструкторов Центра «ВОИН»
В Тюменской области завершился интенсив «Наставники специального назначения», в конце которого спели о связи поколений, защищающих Отчизну.
Автор песни — донецкий инструктор
Максим Сухинин.
@AG_DPR


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User]
📹
Гуманитарная помощь в преддверии дня молодежи для 14 школы Иловайска
Фонд "География сердца" и межрегиональная общественная организация "ВЕЧЕ", при поддержке 1 Донецкого армейского корпуса, доставили в 14 школу Иловайска литературу, а так же учебные пособия, которые необходимы школе для качественной работы. Так же в рамках данной акции общественной организации «от сердца к сердцу» Иловайска были переданы подарки для детей ко дню молодежи.
Подписывайтесь
 на телеграмм канал Народная милиция ДНР, чтобы увидеть войну нашими глазами


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User]
Треш! Ще одна жахлива аварія в Києві

🤯
На проспекті Бандери зіткнулись дві тачки і трактор. Є постраждалі.
UPD:
водій бмв загинув.
Труха
⚡
Київ
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[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User]
«Матрица имеет тебя»
Вчера я посмотрел интересный эфир с одноименным названием, решил подсуммировать сказанное и тем самым углубить свое понимание. Получился следующий конспект. А ссылки на каналы спикеров и на сам эфир оставлю ниже.
Экспансивное потребление — путь человека сегодня.
Такое заключение можно сделать из наблюдений за состоянием вещей в мире:
1 - чем больше ресурсов, тем лучше выживать;
2 - современная экономика держится на потреблении ресурсов, что создает условия занятости и обогащения причастных к процессу.
В то же время - «Суета сует! – сказал Екклесиаст. – Суета сует, все суета!»
Человек, добившийся вершин своего времени, удручен положением дел. Такое ощущение, что человечество - это подрастающий индивид, который пока что занят оформлением «подушки безопасности на старость». Такое ощущение, что у него она уже есть, и пора бы выдохнуть, но мы упорно давим соки дальше, потому что не знаем чем ещё заняться. Хотя проблем в мире больше чем достаточно.
Погоня за миром — бегство от духа.
Существует определение, что человек - это человек досуга. Простив тавтологию, можно заметить разницу между формами существования индивида. Человек разорван, двоякий, двусторонний, связующий, казалось бы, разных миров — материи и духа. Мы слышим то, что диктует нам мир, но странным образом отвечаем ему не так, как остальные животные, и именно это поставило нас впереди планеты всей. В чем дело? Каков наш ответ?
Что за материей? Обратная сторона вещей.
Философия начинается с удивления. Когда-то давно меня поразила, и сейчас обжигает при касании к ней, мысль — а где находится Всё? По-моему, я смотрел на звезды ночью, и задал себе этот вопрос — что есть такое, что больше чем это все, и что его бы уместило? Не меньшее удивление мне подарило осознание что чашка сделана из глины, глина из молекул, они — из атомов, и так далее, а где стоп? Получается странное месиво объяснительных схем — в обе стороны бездна, а тогда, на что опереться?
Сродность «затылков» человека и предметов, или откуда у ножа оттенки?
Странным образом один и тот же предмет может нести разное значение. Одно и то же слово может быть и добрым и злым. А откуда берется окраска? Человек оказывается носителем информации, которую на него «записали». Чего бл*ть!? Вот мы сталкиваемся с поступком, мыслью, предметом, и оно как будто цепляется за нас, почему-то не дает пройти мимо, подсвечивается как важный айтем в игре. Но если предметы и слова сами по себе ничего не значат, то что в нас вызывает отклик на них? И что первично - значение или порядок разрозненных букв? Мне почему-то ощущается что оно приходит откуда-то сзади, поэтому и использовал метафору затылка. Теперь осталось найти этот самый зад…
Канал Дмитрия Пастернака-Таранушенко:
https://t.me/pasternak_taranushenko
Канал Юрия Романенко:
https://t.me/romanenko_dns
Ссылка на эфир:
https://www.youtube.com/live/PU4KusahuXw?si=vF7TmBzpGSpAyZF9


[System]
You are an expert in the fud manipulation technique. FUD (Fear, Uncertainty, Doubt): Sows fear, uncertainty, and doubt to manipulate perception and discourage opposition. List phrases that provide evidence of fud in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the fud manipulation.
To effectively refine your classifier for detecting the Fear, Uncertainty, and Doubt (FUD) language manipulation technique in the provided texts, it is critical to establish clear classification guidelines. We need to reduce false positives by avoiding misclassification of benign or neutral phrases, and reduce false negatives by ensuring timely detection of FUD-related content. Below are recommended guidelines tailored for you:

### Classification Guidelines

1. **Identify FUD Keywords and Phrases:**
   - Search for words that evoke strong emotions related to fear, confusion, or doubt. Examples include:
     - Fear: "страшно", "жах", "катастрофа", "вбивство"
     - Uncertainty: "можливо", "нема гарантій", "неясно"
     - Doubt: "не вірю", "здається", "сумніви", "начебто"
   - Note that while exact matches are useful, variations and derivatives of these words should also be included (e.g., "страх", "боятися", "паніка").

2. **Contextual Analysis:**
   - Evaluate the context in which the keywords are used. A phrase might contain a FUD keyword but could be in a context that is neutral or critical rather than manipulative. For example:
     - Statements like "таке трапляється" or "можливо, це не правда" can often indicate a doubt but should not automatically be classified as FUD if they are providing critical analysis or commentary.
   - Use surrounding words and verbs as signals to determine the intent behind statements.
     - For example, "прогноз" (forecast) or "може" (could) without further stressful qualifiers may signify speculation rather than manipulation.

3. **Sentiment Analysis:**
   - Implement sentiment analysis tools to determine the emotional tone of the statements. FUD language often has a negative sentiment associated with:
     - War, loss, crises, and disasters.
     - Look for shifts in sentiment when certain keywords are clustered together, indicating a potential FUD message.

4. **Avoiding False Positives:**
   - Be cautious with phrases related to future events that do not carry an emotional charge, such as:
     - "невдовзі настане день звільнення Криму" (the day of Crimea's liberation will soon arrive) may not qualify as FUD unless framed within a context of threat or fear.
   - Exclude neutral phrases even if they contain strong words. For example:
     - "введення санкцій – це добре" (the introduction of sanctions is good) should not be classified as FUD despite the gravity of the subject.
   - Regularly update the classifier with new terms and phrases as the prevailing discourse evolves to keep it current.

5. **Recognizing FUD Patterns:**
   - Patterns can help you capture FUD efficiently. For example:
     - Repeated warnings about threats or dangers in close succession can indicate a FUD intent.
     - "знищать", "губити", "загрожує" (destroying, killing, threatening) can be part of FUD linguistic constructs when coupled with an exaggerated tone.

6. **Classification Hierarchies:**
   - Use a tiered classification system that weights phrases according to how strongly they evoke fear, uncertainty, or doubt.
     - Tier 1 (low FUD): Neutral reporting or analysis devoid of emotional undertones.
     - Tier 2 (moderate FUD): Acknowledgement of threats without exaggerated or alarming language.
     - Tier 3 (high FUD): Alarmist statements that clearly seek to induce fear or doubt among the audience.

7. **Continuous Learning:**
   - Regularly test and evaluate your classifier using both false positive and false negative cases. Machine learning algorithms require ongoing adjustments, so use user feedback, expert reviews, and real-world examples to continue improving your model.

By employing these guidelines, your classifier should more effectively identify FUD-related content while minimizing false classifications. This will enable you to respond more accurately to problematic content that seeks to manipulate perceptions through fear, uncertainty, and doubt.

[User] 17 сентября 1939 года СССР вступил во Вторую мировую войну на стороне гитлеровской Германии. Сначала они вместе раздербанили Польшу, потом Сталин напал на Финляндию и захватил страны Балтии. В это время Гитлер оккупировал Норвегию, Данию, Нидерланды, Францию, Бельгию.