sharmaroshan/Twitter-Sentiment-Analysis

It is a Natural Language Processing Problem where Sentiment Analysis is done by Classifying the Positive tweets from negative tweets by machine learning models for classification, text mining, text analysis, data analysis and data visualization

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Established

Implements a complete NLP pipeline including text preprocessing (removing punctuation, special characters, and stopwords), exploratory data analysis with word frequency and hashtag trend visualization, and feature extraction using Bag-of-Words and TF-IDF representations. The project addresses hate speech detection as a binary classification task evaluated on F1-Score, processing tweets through sequential stages from raw text cleaning to model training for racist/sexist content identification.

270 stars. No commits in the last 6 months.

Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

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Stars

270

Forks

128

Language

Jupyter Notebook

License

GPL-3.0

Last pushed

Nov 03, 2023

Commits (30d)

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