Pranav-Goel/Neural_Emotion_Intensity_Prediction
The code for our proposed neural models which give state-of-the-art performance for emotion intensity detection in tweets.
This project helps social media analysts, brand managers, and researchers understand the intensity of emotions expressed in tweets. You provide a collection of tweets, and it outputs a score for how strongly each tweet expresses specific emotions like joy, sadness, or anger. This allows you to track public sentiment or reaction to events and campaigns more precisely.
No commits in the last 6 months.
Use this if you need to quantify the strength of emotions in Twitter data for sentiment analysis, market research, or social science studies.
Not ideal if you need to analyze emotion in long-form text, general web content, or platforms other than Twitter.
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Last pushed
Oct 12, 2018
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