sentiment analysis
it is to test the sentiment categorization performance across different models
Prompt
You are an expert in sentiment analysis with deep knowledge of internet buzzwords, catchphrases, and web novel culture, particularly in Chinese online communities. TASK: Classify the sentiment of each text below as positive, negative, or neutral. CORE PRINCIPLE: Focus on the LANGUAGE and emotional state conveyed by the writer, NOT your personal reaction to the content. DEFINITIONS: - positive: The text contains explicit or implicit clues suggesting the speaker is in a positive emotional state (happy, amused, admiring, relaxed, forgiving, entertained, etc.) - negative: The text contains explicit or implicit clues suggesting the speaker is in a negative emotional state (sad, angry, frustrated, anxious, disappointed, critical, etc.) - neutral: The text primarily states facts without clear emotional indicators, or contains balanced/mixed emotions that don't lean clearly positive or negative SPECIAL CONSIDERATIONS: - Pay attention to sarcasm, irony, and internet slang - Consider emoticons and their emotional context - Recognize pop culture references and memes OUTPUT FORMAT: For each numbered text, respond with: Text [number]: [positive/negative/neutral] TEXTS TO CLASSIFY: Text 1: 吃饱了自然就没心思追你了。 Text 2: 最后这一页，我两年前做梦梦到过，内容一模一样。这算超能力嘛 Text 3: (ಡωಡ)hiahiahia脱缰的野驴笑死我了 Text 4: 龙傲天赵日天表示不服 Text 5: 齐先生，你怎么开始抽烟了。。。哦，抱歉，走错片场了 Text 6: 鼻孔通不通无所谓吧？只要嘴没事就行 Text 7: 黔驴技穷？呵呵，现在还真是炒剩饭的年代啊！ Text 8: 黑面包的面粉里面纯面粉含量太低，不过度发酵根本发不起来。然而，过度发酵的面团就是发酸的。 Text 9: 黑雾？？？隔壁的穷神二五仔？？？ Text 10: 黑锅大侠首次闪亮登场 Sentiment Analysis:
Response not available
