TarikKaanKoc/IMDB-Sentiment-Analysis-NLP

IMDB dataset having 50K movie reviews for natural language processing or Text analytics. This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training and 25,000 for testing. So, predict the number of positive and negative reviews using either classification or deep learning algorithms

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Experimental

This project helps you understand the overall sentiment expressed in movie reviews. You input a large collection of text-based movie reviews, and it tells you how many are positive and how many are negative. It's designed for data analysts, researchers, or anyone interested in automatically categorizing audience opinions from textual feedback.

No commits in the last 6 months.

Use this if you need to quickly determine the general sentiment (positive or negative) from a large volume of customer feedback or user comments, specifically for movie reviews.

Not ideal if you need nuanced sentiment (e.g., neutral, mixed emotions) or sentiment analysis for domains other than movie reviews.

movie-reviews customer-feedback opinion-mining text-analytics market-research
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 0 / 25

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Language

Jupyter Notebook

License

Apache-2.0

Last pushed

Jul 16, 2022

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