BertSentimentClassification and IMDb_Sentiment_Analysis_BERT

Maintenance 0/25
Adoption 5/25
Maturity 16/25
Community 7/25
Maintenance 0/25
Adoption 6/25
Maturity 16/25
Community 0/25
Stars: 10
Forks: 1
Downloads: β€”
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 16
Forks: β€”
Downloads: β€”
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About BertSentimentClassification

pitmonticone/BertSentimentClassification

BERT Sentiment Classification on the Large Movie Review Dataset.

This project helps anyone who needs to quickly understand the overall sentiment of written text, like movie reviews. You feed it a text, and it tells you whether the author expresses a positive or negative opinion. It’s perfect for market researchers, product managers, or content analysts who deal with large volumes of customer feedback or user-generated content.

sentiment-analysis text-categorization customer-feedback market-research content-analysis

About IMDb_Sentiment_Analysis_BERT

InPhyT/IMDb_Sentiment_Analysis_BERT

BERT Sentiment Classification on the IMDb Large Movie Review Dataset.

This project helps entertainment industry analysts, marketers, or film critics understand public opinion by automatically classifying movie reviews. You input raw movie review text, and it outputs a prediction of whether the sentiment is positive or negative. It is designed for anyone needing to quickly gauge audience sentiment from large volumes of text.

movie-review-analysis audience-sentiment text-classification entertainment-marketing public-opinion-research

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