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Project NewsLens analyzes sentiment polarity from various news sources across topics based on past articles. This aggregated polarity highlights potential bias on specific topics. Users can explore articles, view sentiment, and receive alternative perspectives to form a more comprehensive opinion.

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Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
Research		Research
Result Analysis		Result Analysis
Scraping		Scraping
Targeted Sentiment Classification		Targeted Sentiment Classification
Topic Modelling		Topic Modelling
config		config
README.md		README.md

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NewsLens

Data Driven approach for analyzing news article polarization

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Project NewsLens analyzes sentiment polarity from various news sources across topics based on past articles. This aggregated polarity highlights potential bias on specific topics. Users can explore articles, view sentiment, and receive alternative perspectives to form a more comprehensive opinion.

nlp machine-learning news big-data data-visualization named-entity-recognition topic-modeling newsapi webscraping targeted-sentiment-classification

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