sismetanin/emosense-semeval2019-task3-emocontext
Deep-learning system presented in "EmoSence at SemEval-2019 Task 3: Bidirectional LSTM Network for Contextual Emotion Detection in Textual Conversations" at SemEval-2019.
This project helps customer service teams, social media analysts, or user researchers understand the emotional tone of text conversations. It takes a series of text messages, like a customer support chat or social media thread, and identifies the specific emotion expressed in each message. The output helps users quickly gauge sentiment and respond appropriately.
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Use this if you need to automatically detect and classify emotions (like joy, sadness, anger) within multi-turn text conversations or chat logs.
Not ideal if you only need general positive/negative sentiment analysis, or if your primary focus is on detecting emotions in single, isolated sentences rather than ongoing dialogues.
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Jul 09, 2019
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