SannketNikam/Emotion-Detection-in-Text
This project employs emotion detection in textual data, specifically trained on Twitter data comprising tweets labeled with corresponding emotions. It seamlessly takes text inputs and provides the most fitting emotion assigned to it.
This helps social media managers, customer service analysts, or marketing professionals quickly understand the emotional tone of written content. It takes any piece of text as input and tells you which of eight emotions (like anger, joy, or sadness) is most strongly expressed. You get a direct emotional label, helping you gauge public sentiment or customer feelings at a glance.
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Use this if you need a quick, automated way to identify basic emotions within short pieces of text, especially for social media posts or customer comments.
Not ideal if you require nuanced emotional understanding, highly accurate detection for critical decisions, or analysis of very long, complex documents.
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Last pushed
Oct 29, 2024
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