i-benjelloun/text_emotions_detection
Detection of fine-grained emotions in texts
This project helps social media analysts and marketers understand the nuanced emotional tone of text. You provide social media comments or text messages, and it identifies up to 27 distinct emotions like 'amusement,' 'anger,' 'sadness,' or 'optimism' present in the text. This allows for deeper insights into public sentiment beyond simple positive or negative categorization.
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Use this if you need to detect a wide range of specific emotions in English text, especially from social media, for detailed sentiment analysis or to identify distress.
Not ideal if you only need basic positive/negative sentiment, require real-time processing of massive text streams, or work with languages other than English.
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Last pushed
Apr 06, 2021
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