rohanrao619/Twitter_Sentiment_Analysis
Sentiment classification using a Bi-LSTM network. Uses NLTK for corpus preprocessing and GloVe for word representation.
This project helps social media analysts or marketers automatically sort raw tweets into 'positive' or 'negative' categories. You feed it a collection of tweets, and it outputs a classification for each tweet, helping you quickly understand public sentiment without manual review. This tool is for anyone needing to gauge opinions expressed on Twitter at scale.
No commits in the last 6 months.
Use this if you need to quickly classify a large volume of tweets as positive or negative to understand public perception or trend sentiment.
Not ideal if you need a more nuanced sentiment analysis (e.g., neutral, mixed, or specific emotion detection) beyond simple positive/negative.
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7
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6
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Dec 05, 2020
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