merb92/Twitter-Sentiment-Analysis

Monitor the reception of a new mobile phone on Twitter to help a business reduce its risk of failure and improve product quality using Machine Learning Sentiment Analysis

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Experimental

This project helps businesses understand how customers feel about a new product launch, like a mobile phone, by analyzing public Twitter posts. It takes raw tweets and categorizes them as positive, negative, or neutral. Product managers, marketing teams, or market research analysts can use this to gauge public reception.

No commits in the last 6 months.

Use this if you need an automated way to monitor public sentiment towards your product on Twitter and want early warning signs of negative reception or opportunities to improve.

Not ideal if you need highly accurate, nuanced sentiment classification for complex text data, or if you need to analyze sentiment from platforms other than Twitter.

product-launch social-listening market-research brand-monitoring customer-feedback
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 16 / 25

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Jupyter Notebook

License

Last pushed

Feb 12, 2021

Commits (30d)

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curl "https://pt-edge.onrender.com/api/v1/quality/nlp/merb92/Twitter-Sentiment-Analysis"

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