venkat-0706/Sentimental-Analysis

Build a model to classify text as positive, negative, or neutral. Apply NLP techniques for preprocessing and machine learning for classification. Aim for accurate sentiment prediction on various text formats.

27
/ 100
Experimental

This project helps marketing agencies understand public opinion about a brand or product. It takes social media posts, like tweets, and determines if the sentiment expressed is positive, negative, or neutral. The output is a classification model and a report with insights, enabling marketers to refine their strategies to better connect with their target audience.

No commits in the last 6 months.

Use this if you need to quickly gauge public perception and adjust your marketing messages based on what customers are saying online.

Not ideal if you need to analyze highly nuanced language, sarcasm, or complex discussions that go beyond simple positive/negative/neutral categorization.

marketing social-listening brand-management customer-feedback market-research
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 5 / 25

How are scores calculated?

Stars

18

Forks

1

Language

Jupyter Notebook

License

MIT

Last pushed

Aug 16, 2024

Commits (30d)

0

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