armintabari/Emotion-Detection-RNN
A bidirectional GRU model to detect discrete emotions in tweets.
This tool helps social media analysts or marketers understand the emotional tone of text, specifically tweets. You input a collection of tweets, and it outputs predictions about the discrete emotion expressed in each tweet. This is designed for researchers or practitioners who need to categorize feelings like joy, sadness, or anger from social media data.
No commits in the last 6 months.
Use this if you need to train a custom model to identify specific emotions in a large dataset of tweets, tailoring it to your unique data.
Not ideal if you need to analyze emotions in text other than tweets or want a ready-to-use API without custom model training.
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22
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5
Language
Python
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Last pushed
Jul 22, 2020
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