[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
Командувач 58-ї загальновійськової армії ППО ЗС РФ генерал-майор Іван Попов записав звернення у стилі Пригожина -
аудіоповідомленням на 4 хвилини
. У ньому повідомив що його виперли з посади.
Ми уже послухали цей подкаст за вас - він розповідає, що його поперли бо він, ніби-то, розказав своїм начальникам правду про те, що у росіян на фронті все погано.
Тут як не крути, одні плюси:
1. Поперли - добре
2. Якщо те, що він сказав  - правда - теж добре.


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
Нардеп от «Слуги народа» Анна Пуртова опубликовала фотографию с Залужным с подписью:
"Cкоро всё узнаете".
Шептун
 |
Instagram
 |
Facebook


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
Канал создан для архивирования док файлов боевых действий с обоих сторон в секторе Ясиноватского района вне зависимости от предпочтений кто и что хотел бы видеть.
По предпочтениям переходите по ссылкам на соответствующие каналы. Они все известны.
Присылайте любые видео по Ясиноватскому  сектору в канал для публикаций.
"Нытьё" воспринимается каждым субъективно на индивидуальной основе в результате складывающегося  анализа информации.
Подскажи с какого пальца высосать по Ясиноватскому району то, о чём ты пишешь.
Или у какого военкора или военлёта/блогера "утянуть" с канала ?
Жду ссылок.
Публикую моментально.
Ps
"Люблю смотреть" будучи штурмовиком
Pps
Режет слух эта лабуда


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
🇺🇦
Наше військо потребує відважних і рішучих. Долучайтеся до лав Десантно-штурмових військ Збройних Сил України та станьте частиною рушійної сили, яка змінить хід історії.
Заповніть анкету за посиланням і розкажіть про свою професію. Ваші цивільні навички можуть допомогти наблизити перемогу
👇
https://godshv.mil.gov.ua/
Командування Десантно-штурмових військ Збройних Сил України
🇺🇦

Telegram ЛОВА
 /
🇺🇦

Сайт ЛОВА
 /
🇺🇦

Facebook ЛОВА
 /
🇺🇦

Instagram ЛОВА
 /
🇺🇦

Twitter ЛОВА
 /
🇺🇦

WhatsApp ЛОВА


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
Бондар то одвічний дух коліївщини.
Я сам його телеграм читаю примружуючі очі. Такий щирий страшний потік правдорубства та ненависті
🤣
🤣
🤣
Недарма перелом заробив у Северодонецьку
😂
Думали паралізує, але бачите.
Така люта мила нєрпа, що вижив! Веселий і бадьорий
😂
Рекомендую:
https://youtu.be/Nu3i8KzF-gA


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
#засідання_уряду
🟡
Денис Шмигаль провів засідання Уряду щодо рятувальної операції через терористичний акт рф на Каховській ГЕС
Прем’єр-міністр розповів, що Кабінет Міністр оперативно реагує на усі виклики, що постали перед Україною через підрив окупантами Каховської ГЕС.
Зокрема, Уряд вже виділив сумарно 2,4 млрд грн для забезпечення водою жителів Херсонської та суміжних областей.
Денис Шмигаль поінформував, що наразі в Україні працює штаб з ліквідації наслідків аварії на чолі з головою МВС:
«Задіяно 1400 осіб та 345 одиниць техніки. На Херсонщині розгорнули 9 евакуаційних пунктів, евакуювали станом на сьогодні 2,3 тис. людей, організували підвіз питної води».
Окрім того, очільник Уряду закликав світ реагувати на катастрофу Каховської ГЕС діями, а не словами.
«По-перше, визнати очевидне – саме росія є відповідальною за підрив. По-друге, закликаємо до інтенсивної допомоги Україні, щоб мінімізувати наслідки катастрофи», – заявив Денис Шмигаль.
Він розповів, що згідно з даними Міндовкілля, екологічні збитки обчислюються в розмірі більше 55 млрд грн.
За його словами, лише на Правобережжі затоплено 10 тис. га с/г земель. Після сходження води потрібно відновлювати ґрунти та понад 30 систем зрошення.
А відновлення ГЕС, за попередніми даними Укргідроенерго, коштуватиме орієнтовно 1 млрд євро. Ще стільки ж коштуватимуть інші супутні роботи.
Інформація від
#Кабміну


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
🌐
 На минулому тижні в Україну повернувся Світовий Банк. З початку війни їх офіс був у Відні і зараз, нарешті, вони знову відкрили постійний офіс в Києві.
World Bank - це дуже добрий знак не тільки для нас, але для всіх інших великих фінансових інституцій. МВФ досі не оголосили про свої плани повернутися.
🤔
 Але є ще один момент: буде значно-значно більше контролю за іноземними грошима.
🗓
 В цілому, я від багатьох послів G7 та очільників міжнародних донорів чую, що з другої половини 2023-го року починається нова фаза. Фаза, коли безумовна фінансова підтримка закінчується.
І далі все більше буде тільки
 «
💵
гроші  в обмін на реформи»
.
Особливо американські гроші. І так, скоріше людей у владі, які патологічно крадуть такі гроші, доведеться швидко десь загубити.
💁♂
А перелік таких і де саме крадуть ми кожен тиждень надаємо)


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
Бахмут: реальна історія штурму
Атаку вагнерів зупиняє лише загороджувальний вогонь. За годину смертники наступають знову, і так по колу.
Це третє
відео
 з серії військової хроніки про оборону міста.
Виняткова витримка бійців
2-го батальйону,
 перехоплення ініціативи штурму та відмінність тактики зеків від загонів росармії.
Правда про бахмутські бої — дивіться на нашому
YouTube!
3ОШБр
 |
Instagram
 |
Facebook
 |
YouTube
 |
ab3.army
 |
SupportAZOV
🇺🇦


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
а других охранителей у меня для вас нет
https://peremogi.livejournal.com/67292064.html
#ненаши

#кредитная история

#аберрация сознания

#картинка

#не всё так однозначно

#патриотическая перемога


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
⚡
Пентагон умоляет уволенных за отказ от вакцинации от COVID солдат вернуться на службу
Два года назад Пентагон безжалостно увольнял за отказ от вакцинации уверяя, что это не повлияет на боеспособность армии. Больше всего подвергся увольнениям корпус морской пехоты, из которого выгнали 1968 человек. Более 17 тыс. военнослужащих отказались от прививок, ссылаясь на опасения по поводу безопасности вакцины, связанные с ее быстрой разработкой.
Кроме того, тысячи потенциальных призывников отказались поступать в вооруженные силы, потому что не желали получать вакцины от COVID.
Мандат на вакцинацию от COVID вывел из строя в три раза больше военнослужащих (8339) по сравнению с войной в Афганистане (2402).
Теперь военнослужащим предлагают вернуться на службу и даже исправить их записи в личных делах, испорченные сведениями о невыполнении приказа вакцинироваться.
Дошло. Лучше поздно, чем никогда!


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
СБУ ліквідувала у Кропивницькому ботоферму, яка створила понад 3 тисячі фейкових акаунтів для інформдиверсій проти України
Кіберфахівці Служби безпеки нейтралізували у Кропивницькому ботоферму, яка діяла на користь російських спецслужб.
У результаті слідчо-оперативних дій затримано організатора ворожого «осередку». Ним виявився переселенець із Запоріжжя, який переїхав на Кіровоградщину після початку повномасштабного вторгнення.
Там він розпочав масово створювати анонімні акаунти у соцмережах і продавати їх через даркнет. Відповідне обладнання встановив в орендованій квартирі одного зі спальних районів обласного центру
Середня вартість одного боту – 200 грн.
Встановлено, що зловмисник створив майже 3 тис. фейкових акаунтів, які планував продати на загальну суму більше ніж пів мільйона грн.
Основними його «клієнтами» були представники російських спецслужб, а також підконтрольні їм прокремлівські пропагандисти.
Боти потрібні були агресору для «розгону» дезінформації нібито від імені українських громадян про ситуацію на фронті, а також для спроб дискредитації підрозділів Сил оборони.
Таким чином ворог намагався розхитувати внутрішньо-політичну обстановку в різних регіонах України в умовах війни.
Під час обшуку в орендованій квартирі фігуранта виявлено:
▪
 комп’ютерну техніку;
▪
 спеціалізоване обладнання;
▪
 3 тис. SIM-карток, які він використовував у протиправній діяльності.
Наразі слідчі Служби безпеки повідомили зловмиснику про підозру за ст. 436-2 (виправдовування, визнання правомірною, заперечення збройної агресії рф проти України, глорифікація її учасників) Кримінального кодексу України.
Вирішується питання щодо додаткової кваліфікації злочинних дій фігуранта та обрання йому міри запобіжного заходу – тримання під вартою.
Заходи проводили співробітники СБУ за процесуального керівництва обласної прокуратури.


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
- По поводу отрезанных голов наших солдат.
Мы что не знали, что воюем с пидарасами?
Это не первый, и, увы, не последний такой случай.
Для таких случаев у нас есть дипломатия и спецслужбы.
Дипломатия даст свою оценку (уже дала).
Дмитрий Кулеба:
- Государство хуже ИГИЛ, председательствует в ООН и это - абсурд.
Спецслужбы взялись найти и привлечь к ответственности (Василий Малюк).
Мы, общество, должны дать свою оценку.
Дали - «пидарасы».
Нам также нужно понимать - для чего вбросили прошлогодние случаи в сеть именно сейчас.
Одна из версий:
- устрашить наших,
- спровоцировать наших на жестокость,
- устрашить своих,
…перед контрнаступлением.
А наша, общества задача - сделать возможное, чтобы об этом случае и нашей оценке узнали как можно большее количество людей, особенно, иностранцев.
Сделали?..


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
📌
 Невдовзі парламент голосуватиме законопроєкт про медичний канабіс.
Від імені лікарської спільноти та десятків тисяч пацієнтів, яким може допомогти ця речовина, хочемо нагадати законотворцям: медичний канабіс – це ліки!
Це визнані у 56 країнах світу ліки для понад 50 патологічних станів: хронічному болі, артриті, ревматизмі, епілепсії, хворобах Альцгеймера і Паркінсона, діабетичній нейропатії, різних форм склерозу тощо. Крім того, медичний канабіс необхідний онкопацієнтам, для яких страшний біль – щоденна реальність.
Прийняття законопроєкту №7457 – це навіть не йти в ногу з сучасними медичними практиками, це питання виживання для багатьох українців, які стали жертвами війни. Війни, яка досі триває і жертв якої з кожним днем більшає.
Прийняття Закону №7457 – це акт милосердя для тих, хто потребує цих ліків.
❗
 Позиція Міністерства охорони здоровʼя у цьому питанні чітка та однозначна. Медичний канабіс – це ліки!
❗

Просимо народних обранців дослухатись до думки професіоналів, робота яких полягає у порятунку життів, та проголосувати ЗА законопроєкт №7457.
#знеболь7457

Автори фото:
Костянтин та Влада Ліберови


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
СМИ: Тысячи военных перебросили ВСУ в Одесскую область для подготовки провокации против Приднестровья
Сообщается, что с начала марта в районах н. п. Дачное, Каменка и Раздельная местные власти начали передавать ангары (для хранения сельхозпродукции) ВСУшникам для размещения личного состава и техники.
🪖
 За апрель туда направили до 4 тыс. военнослужащих.
Боевики, вероятно, размещаются в этих ангарах и раз в два-три дня меняют места дислокации.
🏴

Предположительно, с 9 по 15 мая одна группировка ВСУ планирует выдвинуться в направлении Тирасполя, чтобы начать вооруженную провокацию для отвлечения российских войск.
❗
 Вторая группа нацистов, скорее всего, попытается захватить склады с боеприпасами в селе Колбасна.


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
⚡
 Захар Прилепин введен в кому для того, чтобы быстрее восстановиться, сообщил губернатор Нижегородской области Глеб Никитин.


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
Марат Хуснуллин: В новых регионах страны будет сформирована сеть федеральных трасс
Более 1 тыс. км дорог в новых регионах получат статус федеральных в 2023 году, сообщил вице-премьер Марат Хуснуллин.
«1039 км автодорог в ДНР, ЛНР, Запорожской и Херсонской областях получат статус федеральных в 2023 году», — написал он в Telegram.
Хуснуллин уточнил, что в новых регионах России будет сформирована сеть федеральных трасс.


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
🇫🇮
Фінляндія передала Україні 19-й пакет військової допомоги на €95 млн — Міноборони Фінляндії
Фінляндія дуже радує. З її населенням в 5.5 млн це взагалі дуже потужно
🦅
Kravchuk


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

[User]
#працюєГУР
⚔

Спецпідрозділ ГУР «КАБУЛ 9» віртуозно знищує ворога
❌
 Спецпідрозділ Головного управління розвідки Міністерства оборони України «КАБУЛ 9» виявляє та знищує російських загарбників у Запорізькій області.
💥
 На відео ― результати успішного вогневого ураження 2 вантажних автомобілів та баггі російських загарбників, а також стартової позиції FPV-дронів окупантів, де перебували ворожі оператори.
☑
 Втрати противника уточнюються.
👥
 Спецпідрозділ «КАБУЛ 9»  виник на початку широкомасштабного російського вторгнення. Його сформували ветерани українських спецслужб та ЗСУ за сприяння та участі начальника ГУР МО України Кирила Буданова.
🇺🇦
 Спецпідрозділ брав участь у битві за Київ у Гостомелі та на Броварському напрямку.
Мінометні розрахунки та снайперські групи підрозділу української воєнної розвідки також працювали під час оборони Бахмута.
🫡
 Зараз розвідники-спецпризначенці продовжують воювати проти російських окупантів на півдні України.
ГУР в інших соціальних мережах:

🔹
Facebook

🔹
YouTube

🔹

Viber

🔹
Instagram

🔹
Twitter

🔹

Threads

🔹

WhatsApp
🔹

Telegram Bot
🔹

TikTok


[System]
You are an expert in the loaded_language manipulation technique. Loaded Language: Employs strongly emotional or charged words to sway opinion. List phrases that provide evidence of loaded_language in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the loaded_language manipulation.
To improve the classifier's performance in identifying the use of loaded language effectively, addressing the observed false positives and false negatives is crucial. Here are some tailored classification guidelines you can follow:

### Guidelines for Identifying Loaded Language

1. **Understand Emotional Connotations**:
   - Loaded language often contains words or phrases that evoke strong emotions (anger, fear, pride, hope). It is essential to focus on the emotional valence of specific words rather than their dictionary definitions.
   - Words like "aggression," "oppression," "hero," "struggle," "victories," or "tyranny" carry significant emotional weight. Identify and flag such emotions in the context compared to neutral language.

2. **Context Matters**:
   - Evaluate the context in which words are used. For example, "responsibility" might be neutral in some contexts but might turn charged when discussing obligation in a war scenario.
   - Understand idiomatic expressions or phrases that may sound neutral but hold connotations in a specific context (e.g., "defend," "combat," "struggle for freedom").

3. **Identify Power Dynamics**:
   - Loaded language often reflects power dynamics, such as terms that undermine opponents or elevate allies. Look for language that labels individuals or groups negatively (e.g., "occupied" vs. "liberated").
   - Watch for descriptors that reinforce or challenge authority, such as "heroic" for allied forces or "tyrants" for opposing ones.

4. **Differentiate Between Facts and Narrative**:
   - Loaded language usually blends factual statements with subjective judgment or a narrative. Distinguish pure facts from interpretative statements.
   - Avoid flagging statements that are purely factual (like citing a number of casualties) unless accompanied by a subjective or emotional angle.

5. **Watch Out for Hyperbole**:
   - Loaded language can include exaggerated statements used for emphasis. Phrases like "massive loss," "unprecedented destruction," or "complete victory" can evoke strong emotional responses.
   - Identify potential hyperboles that shift the tone of the text dramatically.

6. **Recognize Patterned Language**:
   - Identify recurring phrases or terms that express similar sentiments across various documents. Loaded language often follows a pattern in how certain ideas are framed (e.g., "sacrificing for freedom").
   - Use linguistic analysis tools to detect common phrases associated with loaded language.

7. **Test for Binary Classification**:
   - Implement a system that categorizes phrases as either loaded language or neutral based on their emotional impact. Use a manual review process for ambiguous cases where AI misclassifies critical language as neutral.
   - For example, if a document states, "The soldiers bravely defended the city while facing overwhelming odds," flag it as loaded due to the valorisation of soldiers.

### Addressing False Negatives
- Pay close attention to phrases that may appear neutral but are contextually important for the overall sentiment (e.g., "The need for defense equipment is crucial during this time").
- Analyze statements that reference significant events, tragedies, or losses but are framed neutrally, as they can carry emotional weight in specific contexts.

### Addressing False Positives
- Implement rules or heuristics to detect and filter out terms that are commonly used in legal or military discourse without emotive connotations (like "responsibility" or "mobilization").
- Use more specific contextual cues by analyzing surrounding language to ensure a more refined understanding of potential loaded versus neutral expressions.

By focusing on these guidelines, you can enhance your classifier to more accurately detect loaded language while reducing the misclassification of terms that appear impartial. It's a combination of nuanced linguistic analysis and sensitivity to context that will yield better results.

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