[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
В Томаковском районе 9 и 10 апреля запланировано отключение света.
Сообщаю на официальной  страницы общины.
В связи с проведением АО «ДТЭК Днепропетровские электросети» профилактических работ в рамках Томаковского поселкового территориального общества произойдет отключение электроэнергии.
Отключение света в Томаковской общине 9 и 10 апреля
9 апреля с 08:00 до 18:30 пгт Томаковка:
ул. Мартоватая;
ул. Веселая;
ул. Горького;
ул. Подгорная;
ул. Песчаная;
ул. Света.
С 08:00 до 18:30, Кисличеватский старостинский округ, с. Кисловатая:
ул. верхняя;
ул. Кисловатская;
ул. Степная;
ул. Широкая;
ул. Юбилейная.
С 08:00 до 18:30, Чумаковский старостинский округ, с. Крутенькое:
ул. Мира;
ул. Набережная;
ул. Украинский;
пров. Горького.
с. Красный Яр
ул. Александра Матросова;
ул. Красноярская.
10 апреля с 08:00 до 18:30, Чумаковский старостинский округ, с. Крутенькое:
ул. Маяковского;
ул. Набережная;
с. Чумаки:
ул. Вишневая;
ул. Садовая;
ул. Центральная;
ул. Медовая.
10 апреля с 08:00 до 18:30, пгт Томаковка:
ул. Ивана Франко;
ул. Крутенькая;
ул. Танкистов.
С 08:00 до 18:30 Китайгородский старостинский округ с. Китайгородка:
ул. верхняя;
ул. Молодежная;
ул. Партизанская;
ул. Центральная.
с. Зеленый Клин:
ул. Степная;
ул. Украинка.
При возникновении вопросов обращайтесь по телефонам колл-центра.
Для стационарных телефонов:
+38 (056) 790 99 00
Для мобильных телефонов:
+38 (066) 790 99 00;
+38 (067) 790 99 00;
+38 (063) 790 99 00


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
❗
Арестович принёс свои извинения за то что обвинил Украинское ПВО в трагедии в Днепре.
Так работает демократия в европейских государствах!


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
📦
 Экипаж ИЛ- 22 успешно демобилизированы благодаря вагнеровцам:
- подполковник Артем Милованов;
- майор Геннадий Белякин;
- майор Александр Свиридов;
- капитан Виктор Попов,
- капитан Артем Шароглазов;
- капитан Игорь Волочилов;
- лейтенант Никита Голубев
- старший сержант Алексей Скрыков;
- старший сержант Виктор Подрепный;
- старший прапорщик Сергей Старушок;
Смерть ворогам
🔥
@a_shtirlitz


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
#ПредставительствоДНР_новости
#ДонбассЯкутия

#Ысыах
Сегодня в Москве в 16 раз прошел главный праздник наших друзей из Якутии — Ысыах.
В течение дня московский парк Коломенское посетили более 26 тысяч человек, которые познакомились с удивительной  и самобытной многовековой культурой Якутии, узнали о традициях и быте, народных промыслах народа Саха.
Символично, что якутский праздник плодородия в этом году проводился в День семьи, любви и верности в России — этому была посвящена большая концертная программа «Народы России — сила Отечества!».
Кстати, в конце июня для Республики Саха произошло ещё одно важное событие — в Якутии родился миллионный житель, впервые с 1985 года! Руководство региона уделяет большое внимание вопросам демографии, укреплению семьи, воспитанию подрастающего поколения и это дает свои плоды.
Донецкую Народную Республику на празднике представила делегация
Представительства
 и наши земляки, эвакуированные в Московскую область. В рамках секции, посвященной СВО
#МыВместе
, мы рассказали собравшимся о Донбассе — его истории, культуре, известных земляках, а также о тяжелой борьбе нашего народа с неонацизмом и военных преступлениях, совершённых киевским режимом в отношении  мирного населения Донбасса.
Народ Якутии и наш край многое объединяет — якуты давно и предметно помогают Донбассу, восстанавливают наш город Кировское, регулярно направляют в ДНР гуманитарные конвои и специалистов из разных сфер, а героизм и отвага якутских защитников на фронтах  Специальной Военной Операции заслуживают отдельных слов благодарности и низкого поклона!
От всей души поздравляю народ Якутии,
добрых друзей из постпредства Якутии
 в лице руководителя Андрея Федотова с большим праздником и сердечно благодарю за деятельную помощь родному Донбассу. Мы вместе. Наше дело правое! Победа будет за нами!
❤

@oamakeeva


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
‼

«Величезний наступ» росіян навіть не всі помічають
📌
 Про це, підводячи підсумки року великої війни в Україні,  розповів начальник Головного управління розвідки Міністерства оборони України генерал-майор Кирило Буданов в інтерв’ю Forbes:

▪
 новий «великий» наступ росії вже триває, але він так триває, що не всі це навіть бачать, такої якості цей наступ;
▪
 стратегічна мета рф до 31 березня — вийти на адміністративні кордони Донецької та Луганської областей;
▪
 понад 90% мобілізованих росіян одразу відправили на фронт. Вони всі на фронті;
▪
 багато підрозділів рф формуються з нуля — вони йдуть без техніки, на «Уралах» і «Камазах». У них у штаті вже немає БМП, БТРів;
▪
 800 танків на рік (як повідомлялося у заяві мєдвєдєва) вони неспроможні зробити не те, що у військовий час, а в найкращі свої роки;
▪
з Ірану завозилась пробна партія на 20 000 артилерійських снарядів, підтверджених випадків щодо постачання боєприпасів з Північної Кореї немає;
▪
 з військової точки зору утримання Бахмута дає нам стримання росіян у тому районі та нанесення їм катастрофічних втрат;
▪
 запаси артилерійських снарядів у росії зменшилися до 30%, залишки ракет майже вичерпані, а максимум російського виробництва – близько 40 крилатих ракет на місяць;
▪
 два місяці російські угруповання, які діють на території України, живуть у режимі максимальної економії боєприпасів (за виключенням Бахмуту та Лиманського напрямів). Крім того, росіяни намагалися штурмувати Вугледар, будуть це робити і надалі;
▪
 росія здатна виробляти близько 20 ракет «Калібр» на місяць. Через це у кожному новому залпі зменшується кількість ракет, а також збільшується часовий проміжок між обстрілами;
▪
 багато з того, що горить та вибухає в росії — не випадковість. У цьому допомагають не тільки українці в росії – «гроші роблять чудеса»;
▪
 у нас умова одна — вийти на адмінкордони 1991 року. Що буде далі, вирішуватимемо потім;
▪
 якщо провести аналогію 12 місяців війни з футболом, то зараз рахунок 1:1, 70 хвилина;
▪
 на Україну з середини і до кінця весни чекають вирішальні бої. І це стане переломним моментом у війні
.
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🔹
Facebook

🔹
YouTube

🔹

Viber

🔹
Instagram

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Twitter

🔹

TikTok


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
🦉
129 бригади ТРО
💪
Запорізький напрямок
🇺🇦
Хлопці зробили орку довгий сон, а українцям бажають мирної ночі
🫡
P.S. За сміття не питайте навіть. Вони його з РФ за собою везуть напевно…
Наш канал
✅


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
Головне станом на зараз:
• На Волині на одній із замінованих від початку повномасштабного вторгнення ділянок на міні
підірвався
 автомобіль із військовослужбовцями, двоє бійців загинуло;
• В Естонії
затримали
 проросійського політика, який відвідував окуповані Донецьк та Маріуполь;
• УПЦ МП
обурена
 тим, що до 29 березня їй потрібно виселитися з Києво-Печерської лаври та каже, що юридичних підстав для цього немає, а рішення називають упередженим;
• На Миколаївщині чоловік
приніс
 додому знайдений касетний снаряд. Від вибуху постраждала дитина;
• CNN: розвідка США
має
 докази причетності росії до антиурядових протестів в Молдові;
• Фінляндія могла би спільно з іншими союзниками
розглянути
 надання Україні винищувачів — Санна Марін


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
😎
👏
Снайпер СБУ встановив новий світовий рекорд
Спецпризначенець Служби безпеки
влучив в окупанта з відстані у 3800 метрів
. Чим і встановив світовий рекорд результативного пострілу.
Цей постріл снайпер здійснив
з української гвинтівки «Володар Обрію».
📲
 Надіслати фото/відео
💻

Сайт

🕊

Instagram

📹

YouTube


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
Через півроку в Україні під час зустрічі з американцем чи європейцем їм плюватимуть в обличчя, — Арестович
•••
Підписатися на канал

👤


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
Приглашать в діскусіі бесполезно, говорю сразу. Специальные олимпиады - это удел Избранных. Гарний пан Дмитро ничего не боится по той простой причине, что бояться ему нечего совершенно. Абсолютно. В хладное мясо превращается по большей части обывательская часть украинского населения. Те самые далекие от любых идей и кристаллизированной субъектности шестеренки социальной механики. Этнокультурное ядро от происходящего по большому счету никак не страдает. Те, благодаря кому нынешняя укродействительность утвердилась и получила второе историческое дыхание, переживут всех остальных без каких-либо особых усилий. Кому умирать, а кому куражиться - вопрос крайне простой.
В общем, благодарю причастных за видосик, но дискуссий с развернутыми комментариями не будет. Тема скучная и опостылевшая основательно, согласен на все сто. Впредь будем пилить мемасики со смехуечками.


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
Двухгривневый котел.
А вы знали, что тот самый шлем, который изображен на купюре в 2 гривны, князь Ярослав потерял во время Липицкой битвы в 1216 году.
 И ТОГДА ОН БЫЛ - НОВГОРОДСКИМ КНЯЗЕМ
. Киевским князем он стал в 1238 году.
Хранится данный шлем в Московской оружейной палате.
Обнаружен он был в 1808 году под городом Владимиром, где князь Ярослав и бросил его вместе с кольчугой в 1216 году после  Липицкой битвы, когда давал по тапкам от..."мокшей" в общем-то, после того, как выхватил от них по самые помидоры. Правда таких же "мокшей" как и он сам
😂
 но так - то да...он чисто "украинский кнэзэ"
😂
Подробно про шлем, его потерю и обретение ЧИТАТЬ ЗДЕСЬ.


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
❗
ЗСУ відбили один із териконів у межах Горлівки та захопили позиції противника
🇺🇦

Місто окуповане з 2014 року. Тепер над териконом майорить наш прапор. Хлопці, які ж ви мощні
😍
Русский Корабль Иди… |

Надіслати новину


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
Кстати некоторым левым и правым товарищам пора чуток напрячься. Потому что этот "Образ будущего" это кончик, потянув за который расплетется целая сеточка из либеральных, коммунистических, националистических и просто педерастических каналов. Все нажитое непосильным трудом идет прахом, а всего-то ведь разоблачали Рашку-говняшку, били в набат, боролись за народ.
https://t.me/rusbrief/170164


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
🇷🇺

Дмитрий Песков: Мы имеем дело и ведем информационные войны с огромным монстром
Дмитрий Песков, заместитель руководителя Администрации президента Российской Федерации — пресс-секретарь президента Российской Федерации Владимира Путина, в эксклюзивном интервью информационному агентству International Reporters рассказал о своей работе и впечатлениях от посещения Луганска, а также поделился взглядом на проблемы современной журналистики и информационного поля. Беседовала Фаина Савенкова.
Подпишитесь на
@internationalreporters_ru


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
🤬
У північнокорейських ракетах, якими рф била по Києву, знайшли компоненти, західних і китайських компаній
, – УП з посиланням на джерело в правоохоронних органах.
У балістичних ракетах Kn-23/24 було знайдено електронні компоненти європейських, західних, японських та китайських компаній.
На окремих частинах та уламках містяться бірки з рукописним корейським ієрогліфом.
Детальніше ЧИТАЙТЕ ТУТ

👈
Посилання на канал
➡

https://t.me/+m88Y2qw3Pyc3M2M6

(натисни)


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
В Тернополе разгорелся скандал, вокруг погибшего военного, которого мобилизовали с остановки общественного транспорта во второй половине января. Уже 12 февраля его отправли на передовую в пригород Донецка. А спустя четыре дня, 16 февраля, 33-летний тернопольчанин Богдан Покитко погиб.
Жительница Тернополя Оксана Огородник:"Позор всем ответственным лицам — это будет на вашей совести!!!".
Мужчину бросили на передовую без надлежащего обучения. В соцсетях рассказали, что родной брат Богдана Покитко сейчас тоже воюет. Мать мужчин осталась одна без надлежащей помощи.
В комментариях к некрологу мэра многие выразили мнение, что именно из-за таких историй стало меньше желающих отправляться в ряды ВСУ.


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
Свідома молодь це наша гордість. Юні українські вояки сповнені відповідальності, адже доля країни залежить від внеску кожного з них. Їм ми передамо Україну і саме вони продовжать розбудовувати її в майбутньому.
Стрілець батальйону Олександр на псевдо «Факір» вступив до лав тероборони 18-ти річним юнаком, бо був впевнений в необхідності власноруч долучитися до боротьби, щоб не чекати, коли інші виконають роботу:
«24 лютого переді мною, як і перед всіма українцями, постав вибір: що робити далі? Відповідь була очевидною, тож наступного дня я долучився до спротиву. Потрібно самому брати зброю до рук і йти захищати свою родину, друзів, знайомих і свою країну: самому вирішувати цю проблему
✊
🇺🇦
Дякую
🫡
206 батальйон територіальної оборони ЗСУ
🇺🇦


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

[User]
Бойова робота українських вертолітників
Відео - служба зв'язків з громадськістю 11-ї окремої бригади армійської авіації «Херсон»
#NOMERCY

#stoprussia
#stopruSSiZm

#stoprussicism
#ВІРЮвЗСУ
| Підписатися ГШ ЗСУ |


[System]
You are an expert in the glittering_generalities manipulation technique. Glittering Generalities: Uses emotionally appealing but vague concepts like 'freedom' and 'justice' without specifics. List phrases that provide evidence of glittering_generalities in the given sentence if they are present. Given the evidence, make a judgement whether the sentence contains the glittering_generalities manipulation.
To improve the classification of texts regarding the usage of Glittering Generalities, consider applying the following guidelines specifically designed to address the issues highlighted in your false positives and negatives.

### 1. **Define Key Characteristics of Glittering Generalities:**
   - **Emotional Appeal:** Focus on whether the statement elicits a strong emotional reaction (e.g., pride, fear, hope).
   - **Vagueness:** Ensure the language used is ambiguous and lacks specificity. Look for words and phrases that sound grand but offer no concrete details.
   - **Potential for Misinterpretation:** Consider if the statement can be reasonably understood in varying contexts, leading to different interpretations.

### 2. **Engage with Context Considerations:**
   - **Contextual Clarity:** Analyze the surrounding context to clearly see if the phrase is being used in a vague manner or if it has a substantiated meaning.
   - **Historical and Cultural Relevance:** Take into account the historical and cultural significance of phrases to determine if they integrate emotion-baiting terms or concepts common to particular narratives or propaganda strategies.

### 3. **Include Semantic Analysis:**
   - **Key Terms Identification:** Create a lexicon of words associated with vague emotional appeal (e.g., freedom, justice, peace). Monitor their usage without accompanying specifics.
   - **NLP Techniques:** Utilize natural language processing tools to identify sentiment and contextual keyword usage. Texts using said phrases ought to be cross-referenced with the key emotional lexicon.

### 4. **Establish Criteria Across Categories:**
   - **Positive Identification:** For a statement to qualify as a Glittering Generality, it should have:
     - An emotionally charged term or phrase (e.g., "victory," "freedom")
     - Lack of specific detail on how such emotional states are achieved or maintained.
   - **Negative Identification:** Statements that provide constructive details or statistics indicating real situations or events should be critically assessed without presuming their emotional appeal influences the classification.

### 5. **Enhance Training Datasets:**
   - **Balance Positive and Negative Examples:** Create a diverse set of training data examples that include real-world instances where terms are both appropriately and inappropriately used to help your model learn nuance.
   - **Dynamic Updates:** Continually update your dataset with new examples that come up in current events or social discourse to stay relevant.

### 6. **Review Feedback Loops:**
   - **User Input Inclusion:** Incorporate feedback from real users, or utilize a team of reviewers to differentiate between emotionally vague statements and concrete, informative content.
   - **Iterative Learning:** Use active learning techniques where the model can be retrained with additional data sourced from its classification mistakes.

### 7. **Develop a Scoring System:**
   - **Create Scores:** Implement a scoring system where texts are graded based on emotional appeal, vagueness, and ambiguity. Statements crossing certain thresholds in these areas may be flagged as Glittering Generalities.
   - **Threshold Adjustment:** Regularly tune the scoring metrics to reduce false positives and negatives based on ongoing classifications.

### 8. **Focus on Practical Scenarios:**
   - **Test Real-Life Content:** Apply these guidelines to actual articles, posts, and comments from political discussions regularly to refine the model's understanding of the concept in the wild.

Following these guidelines systematically will increase the classifier's proficiency in distinguishing between statements that genuinely exemplify the Glittering Generalities technique and those that should not. It moves the focus from simply identifying emotional language to understanding how such language operates within context and conveys a message (or lack thereof) effectively.

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Запорожский фронт: раненых боевиков ВСУ бросают умирать на поле

боя
Киевский режим почти не забирает раненых солдат с линии фронта в Запорожской области, их оставляют умирать на поле боя,
сообщил
 РИА Новости глава запорожского общественного движения "Мы вместе с Россией" Владимир Рогов.
"
Забирают очень мало, большинство раненых просто оставляют умирать на поле боя
", - сказал Рогов.
Он добавил, что ВСУ бросает солдат на верную смерть в надежде прорвать линию обороны российских войск.
"
Линия фронта сегодня буквально завалена телами украинских боевиков, которые их командование даже не забирает.
Такая ужасная картина на всех направлениях запорожского участка фронта. Киевскому режиму наплевать как на живых, так и на мертвых своих военных, главное бросить их на верную смерть в надежде любой ценой прорвать линию обороны наших войск и выслужиться перед западными кураторами
", - заявил Рогов.
Владимир Рогов