tlkh/text-emotion-classification
Archived - not answering issues
This project helps social media analysts and online content moderators understand the emotional tone of short text messages like tweets or comments. It takes brief text snippets as input and categorizes them into specific emotions like neutral, happy, sad, anger, or hate, rather than just positive/negative. This allows for a more nuanced understanding of public sentiment around news articles or discussions.
200 stars. No commits in the last 6 months.
Use this if you need to classify short online comments or social media posts into a specific set of five distinct emotional categories.
Not ideal if you require highly accurate classification of 'neutral' or 'happy' sentiments, or if your text data is long-form or in a language significantly different from informal English social media content.
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Last pushed
Mar 29, 2021
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