[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]
⚡
СБУ задержала

мужчину, который готовил подрыв железной дороги в Черкасской области
Также он собирал данные о маршрутах перемещения военной техники, предоставленной иностранными партнерами. Кроме того, фигурант "сливал" россиянам локации системы противовоздушной обороны ВСУ в регионе.
Злоумышленнику грозит наказание до 12 лет тюрьмы.
👉

МОЛНИЯ
|
Прислать новость
 |
YouTube


[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]
Как тонули оккупанты после подрыва рашистами Каховской ГЭС. Очень жестокий рассказ.
https://youtu.be/SJE399PO97o
Жестокий рассказ только потому, что всё это происходило там, где были наши люди.
Премьера через 15 минут. На время премьеры отключим чаты в Телеграме. Ставьте лайки, делитесь этим видео, пишите комментарии, потому на этот ролик в Ютуб очень скоро прилетит очень много жалоб. Рашисты активно будут пытаться его забанить.


[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]
❗
Деякі студенти можуть бути мобілізовані
, – МОН.
Мова йде про
осіб
, які знаходяться у академічній відпустці. Вони фактично не навчаються, отже втрачають підставу для надання відстрочки від призову.
ТРУХА
⚡
Украина
 |
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]
47 бригада в бою.
Зараз бачу
публічний
 конфлікт між Валерієм Маркусом та Іваном Шаламагою. Валерій виклав публічне обвинувачення.
Це їхня справа.
Але бачу як уже інтернет-диванні батальйони почали обзивати Шаламагу «совковий офіцер».
Заткніться, шановні.
За Маркуса додам, що він не тиловий, хоче і пробує приймати участь в діяльності поближче до бою.
А за Шаламагу нагадаю:
«Іван Шаламага (позивний – Бескид) народився та виріс у місті Сколе Львівської області. Він – випускник Львівського ліцею з посиленою військово-фізичною підготовкою імені Героїв Крут і Національної академії сухопутних військ імені Гетьмана Петра Сагайдачного. Іванові був 21 рік, коли вперше після закінчення навчання у 2018-му вирушив на фронт. Разом із побратимами обороняли Світлодарську дугу, Попасну, Новолуганське, Зайцеве, а згодом брав участь у бойових діях в районі Вуглегірської ТЕС.
У свої 25 Бескид уже отримав звання капітана Збройних сил України, став наймолодшим командиром полку в історії української армії, а згодом – заступником командира бригади.»
Поранений офіцер про Шаламагу:
«Він дуже грамотний офіцер.
Не сцикун. З яйцями.
Розвинутий фізично, духовно, професійно.
Націоналіст.
Поціновувач традиційних нормальних цінностей».
Євген Карась


[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]
#ДоступніЛіки
Препарати з програми “Доступні ліки”, призначені лікарем, потрібно приймати безперервно. Тому слід контролювати їх наявність та вчасно звертатися за новим рецептом.
📌
Новий рецепт на “Доступні ліки” та інсуліни лікар може виписати до закінчення строку попереднього електронного рецепту:
-за 7 днів, якщо попередній рецепт розрахований на 21 і більше днів;
-за 3 дні, якщо ліків у попередньому рецепті  менш ніж на 21 день.
Тож радимо контролювати кількість лікарського засобу, який залишився і не чекати поки препарат повністю закінчиться, щоб отримати новий рецепт.
📌
Термін дії електронного рецепту становить 30 днів з дати виписування такого рецепту.
На час воєнного стану лікар може виписати як електронний, так і паперовий рецепт. Вони однаково чинні та мають один термін дії.


[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]
Цього красунчика білявого звати Даня. Днями він оформив офіційно свої стосунки в загниваючій Європі.
І все би нічого, але його прізвище Соловйов, а його батька звати Володимир
🤗
Мабуть збіг
😃


[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]
Троє воїнів із Полтавщини повернулися з полону!
Старший солдат ЗСУ Максим Глушко із Кременчуцького району потрапив у полон у Маріуполі.
Молодший сержант, командир відділу Нацгвардії Іван Срібний із Семенівської громади полонений на Запоріжжі.
Солдат ЗСУ Артем Стребко з Новосанжарської громади потрапив у полон на Донеччині.
Нині вони перебувають на реабілітації та тримають зв’язок із рідними.
Загалом, учора був один із найбільших обмінів полоненими. Додому повернулися 230 українських воїнів із різних підрозділів. Багатьох вважали зниклими безвісти. Тож для рідних учора було справжнє свято, дізнатися, що батько, син чи брат – живий!
Вітаємо наших захисників удома!
🇺🇦


[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]
29 вересня Кабінет Міністрів України прийняв рішення щодо вдосконалення механізму подачі заявки до резерву для державної служби на деокупованих територіях.
Охочим долучитися до кадрового резерву більше не потрібно буде проходити мотиваційний опитувальник і тест на загальну ерудицію.
Заповнювати анкету відтепер можна лише українською мовою. За достовірність інформації відповідатиме особа, яка її подала.
Нагадаємо, що платформа резерву державних службовців для деокупованих територій працює в Україні вже майже 3 місяці. За цей час у системі зареєстровано вже близько 2 тисяч анкет від охочих приєднатися до відновлення України. З них: 1795 зараховано, 198 відхилено; 1131 анкету подали чоловіки, 866 анкет - жінки.  Більшість обирає для майбутньої роботи саме Крим, хоча також є можливість обрати всі регіони, які перебувають або перебували під окупацією: Луганщину, Запоріжжя, Харківщину тощо.

Стати частиною резерву відновлення можна шляхом заповнення анкети на порталі НАДС:
https://reserve.nads.gov.ua/


[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 в 4му, та 13-14 році я казав, всі ті революції без люстрації через петлю на суку, то таке.
Всі ті люстрації в смітниках, така ж хуйня як і вставання без взуття на лавочки та дорування квітів беркутні...
Якщо всю цю йобань, як і русню, не топити в їх крові, вони повернуться і повертаються.
Я вірю, що як тільки ми закопаємо останнього кацапюру яка прийшла зі зброєю на нашу землю, ми зможемо всю цю йобань яка смокче кров з нашої держави, втопити в їх же лайні.
Бо ці підари повинні лишитися не тільки своїх посад, а і грошей, статків і майна. І їх сім'ї.
Якщо я не прав, то в чому?


[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]
Абсолютно дико наблюдать, как контора сейчас лениво и надменно отгавкивается от публичных обвинений со стороны Приднестровья вместо того, чтобы оперативно развернуть обстоятельную информационную кампанию с опровержениями и надавить на чувствительные точки самих приднестровцев. При том что обвинения фактурные и очень серьезные. И, что хуже всего, не вполне безосновательные.
Пробеб со стороны службы был да еще какой. По факту именно неадекватный наплевательский подход СБУ к работе с агентурой привел к сложившейся ситуации. Использование граждан Украины в качестве агентов внедрения, легендированных, как беженцы, для тех целей, которые изначально возлагались на по итогу раскрытую агентурную ячейку, было само по себе непрофессиональным и неоправданным решением с высокими рисками. И последствия этого решения, которые мы сейчас наблюдаем, если контора спустит все на тормозах, могут перерасти в крупный международный скандал. Никого уже не волнует, что обвинения в покушении – брехня. Мы сами дали марионеточному правительству Приднестровья карт-бланш на то, чтобы теперь поливать нас грязью, как им вздумается, фактически держа в заложниках украинских граждан – реальных беженцев, которых служба фактически подставила под удар, используя как прикрытие для своих операций. Очень советую пересмотреть заявление Красносельского: он в нем открыто подчеркивает, насколько жестко скандал с агентурой может сказаться на украинских беженцах, лицемерно скрывая угрозу за призывом не «устраивать охоту на ведьм».
Думать, что русня упустит шанс разыграть эту карту в удобный момент – суицидальная наивность.
В самой контроре сейчас безусловно полетят головы. Подобные затишья – надежный маркер проводимой работы над ошибками и выявления виноватых. Но, повторюсь, мало просто найти козлов отпущения и назидательно выпороть перед строем. Нужны коренные системные изменения рабочих алгоритмов – это раз. И два – необходима встречная информационная кампания, возможно даже потребуется задействовать какие-то рычаги давления или даже подключить дипломатические средства, но замять инцидент на билатеральном уровне. Просто пукнуть в подконтрольные СМИ, что панч хуйня и вообще это все приднестровские сепары навыдумывали, не прокатит. Потому что под удар попадут украинские граждане.
Сразу скажу, что претензии по типу «а что украинские граждане забыли в проруснявом Приднестровье?» бессмысленны по своей сути. Во-первых, когда поток беженцев хлынул из Украины в ближайшее зарубежье, власти такой расклад вполне устроил, вопрос никто не взял на контроль. Сами люди при этом просто бежали туда, где их были готовы принять, и очень странно теперь надевать белое пальто и винить их за желание выжить и вывезти семьи. Ну и главный аргумент: государство обязано защищать своих граждан независимо от того удобно ему это или нет – это непреложный закон правового демократического государства.


[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]
Мужчина, напавший с ножом на священника Винницкой епархии УПЦ,
состоит на учете в психоневрологическом диспансере
, —
Нацполиция
Задержанному 47 лет, ранее он не имел проблем с законом. Также правоохранители уточнили, что
 ранения священнику он нанес не ножом, а опасной бритвой
.
Подписаться
 /
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]
У цей день, 16 липня, в далекому 1990-му українці прийняли Декларацію про державний суверенітет України. З того часу минуло 33 роки. Багато що відбулось, багато що змінилось.
Але російські полонені досі кажуть, що не очікували такого спротиву та стійкості.
Ну, значить, росіяни так нічого і не второпали: ані тоді, у 1990-му, ані у 1991-му, ані у 2005-му, ані у 2014-му.
Тому зараз маємо знов пояснювати їм зміст тієї Декларації про державний суверенітет від 1990 року
🇺🇦


[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]
Імпорт нафти з РФ до Індії продовжує падати через західні санкції – ЗМІ
https://1news.com.ua/svit/import-nafty-z-rf-do-indiyi-prodovzhuye-padaty-cherez-zahidni-sanktsiyi-zmi.html
Фото: Shutterstock
Імпорт сирої нафти в Індію від Росії зменшується другий місяць поспіль
третій за величиною у світі імпортер і споживач нафти збільшив імпорт іракської нафти, щоб компенсувати падіння імпорту нафти з РФ.
Через санкції імпорт сирої нафти з Росії в Індію зменшується другий місяць поспіль до найнижчого рівня за рік, пише (
https://www.reuters.com/markets/commodities/indias-oil-imports-russia-hit-12-month-low-jan-sanctions-bite-2024-02-01/
) Reuters.
Повідомляється, що третій за величиною у світі імпортер і споживач нафти збільшив імпорт іракської нафти, щоб компенсувати падіння імпорту нафти з РФ.
Імпорт нафти з Росії знизився на 4,2% до 1,3 мільйона барелів на добу. Дані агентства з відстеження суден Vortexa показали зниження видобутку на 9% до 1,2 млн барелів на добу.
“Зменшення знижок на російську нафту порівняно з близькосхідною нафтою, нещодавні санкції США щодо судновласників, які перевозять російську нафту вище за цінову межу, а також зростання танкерних премій унаслідок атак у Червоному морі зробили російську нафту менш привабливою для індійських нафтопереробних заводів останніми місяцями”, – сказала Серена Хуанг, яка очолює відділ аналізу в Азійсько-Тихоокеанському регіоні Vortexa.
За її прогнозами, імпорт російської нафти в Індію в найближчі місяці може скоротитися ще більше.
Зазначається, що торік Індія стала найбільшим покупцем російської морської нафти, яку продавали зі знижкою, оскільки західні країни припинили імпорт після повномасштабного вторгнення РФ в Україну, але у грудні Вашингтон запровадив санкції щодо суден і операторів суден, які перевозять російську нафту, яку продають дорожче 60 доларів за барель. Банкам і постачальникам послуг було запропоновано стежити за тим, щоб вантажі не порушували цінової межі.
Через санкції кілька танкерів, які малидоставляти сиру нафту Сокіл в Індію, були спрямовані в інший бік.
За даними Reuters, у лютому Індія планує отримати щонайменше п’ять партій сирої нафти Сокіл, хоча в січні не отримала жодної.
Раніше повідомлялося, що в морі застрягли 14 танкерів з російською нафтою через санкції США.
Найбільші грецькі компанії припинили транспортування нафти з Росії – ЗМІ
Новини від 1News в Telegram та WhatsApp. Підписуйтесь на наші канали та WhatsApp (
https://whatsapp.com/channel/0029Va8w6ki4dTnLYdcYww13
)
ПІДПИСАТИСЯ на Telegram-канал 1NEWS (
https://t.me/UA_1NEWS
)
Джерело  (
https://ua.korrespondent.net/world/4660558-import-nafty-z-rf-do-indii-prodovzhuie-padaty-cherez-zakhidni-sanktsii-zmi
)


[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]
Продовжуємо допомагати евакуюватися родинам з прифронтових районів
Продовжуємо невпинно працювати над тим, аби цивільні громадяни, які мешкають поблизу лінії фронту, були в безпеці.
На жаль, не в усіх родин є можливість самостійно залишити небезпечний регіон. Тут на допомогу приходять наші патрульні, які виїжджають в такі локації, де ситуація може бути непередбачуваною.
Учора патрульні разом з поліцейськими Торецька евакуювали з Нью-Йорку, що на Донеччині, родину з трьох осіб.
Далі на Дашу та її батьків чекає дорога до безпечніших регіонів країни.
Ми ж продовжуємо працювати заради безпеки громадян!


[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]
Атаки на українські ядерні об’єкти та окупація Запорізької АЕС йдуть у розріз із позицією «ніколи знову».
Як світ та Європа об’єдналися для убезпечення населення від наслідків аварії на ЧАЕС, так само зараз нам потрібні всесвітні зусилля, щоби деокупувати ЗАЕС та передати її під контроль України.
І маємо зробити все можливе, щоби реально ніколи знову не повторити це.
📲

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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]
Кожне покоління має своїх героїв. І абсолютно неважливо, скільки їм років.
Історія двох українських 16-річних хлопців з Бердянська - це історія справжнього героїзму. Тигран Оганнісян та Микита Ханганов, 2006 року народження, загинули як справжні воїни - зі зброєю в руках, відправивши на той світ двох російських підорів.
Незважаючи на свій вік, вони мали мужність зробити вчинок. Не стали відсиджуватись, тікати чи ховатись. Або розповідати, що ця війна їх не стосується.
Це і є характер та сміливість, які мають бути прикладом для поколінь українців.
@MaksymZhorin

👊🏻


[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]
⁎ Як підрозділи інформаційно-психологічних операцій ССО України стали страшилкою для росіян?
⁎ Як потрапляють на службу в ІПСО?
⁎ Чому українці ведуться на ворожі інформаційно-психологічні операції ?
⁎ Вдалі кейси російських підрозділів психологічних операцій у війни проти України.
⁎ Хто є цілями для воїнів ІПСО ССО України?
⁎ Як виглядає «контакт» з противником у іпсошників?
… та багато іншого - в ексклюзивному інтерв’ю воїна, що служить в підрозділі ІПСО Сил спеціальних операцій.
Лінк на повне відео
👉
https://youtu.be/jofr8pSjVlw
Підписуйтесь на наш YouTube канал, ставте лайки та коменти.


[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]
Нацик записал свой последний видосик
😁
 укросвиньи должны знать, что они все сдохнут на Русской земле и это факт.


[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]
🔥
 Сьогодні вдалося знищити усі повітряні цілі ворога!
🤝
 Я дякую усім, хто забезпечив такий результат. Будемо й надалі посилювати нашу протиповітряну оборону, захищаючи українське небо від нечисті!
🇺🇦
 Слава Україні!