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Rotten Tomatoes Movie Review Sentiment Dataset
Entertainment & Media Consumption
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset is a collection of movie reviews from the popular film review website, Rotten Tomatoes. It includes the text of each review along with a label indicating whether the review was classified as "fresh" or "rotten", based on Rotten Tomatoes' unique review aggregation system. This resource is valuable for researchers, data analysts, and machine learning practitioners interested in sentiment analysis and natural language processing. The dataset features reviews from various critics and publications, covering a wide array of films across different genres and languages. It also provides metadata such as movie title, year of release, genre, director, and cast, allowing for exploration into how such factors influence movie review sentiment. The 'fresh' or 'rotten' label makes it ideal for supervised learning tasks, particularly for training and evaluating machine learning models designed to predict movie review sentiment.
Columns
- Freshness: Indicates the sentiment of the review, where "Fresh" signifies a good review and "Rotten" signifies a bad review. This column contains 2 unique values.
- Review: Contains the full text of the movie review. This column contains 339697 unique values.
Distribution
The data file is typically provided in CSV format. It contains 339,697 records, corresponding to the unique review texts available. Specific file size is not provided.
Usage
This dataset is ideally suited for:
- Conducting sentiment analysis on movie reviews.
- Developing and evaluating natural language processing (NLP) models.
- Training machine learning models for text classification, specifically for predicting review sentiment (fresh/rotten).
- Exploring the influence of movie metadata, such as genre, director, or cast, on review sentiment.
Coverage
The dataset's coverage is global, encompassing reviews from a diverse range of critics and publications. It covers a wide variety of movies across different genres and languages. Specific time ranges for the reviews themselves are not detailed, but the dataset was listed on 16/06/2025.
License
CC-BY
Who Can Use It
This dataset is intended for:
- Researchers: To conduct academic studies on sentiment analysis, NLP, and media consumption trends.
- Data Analysts: For exploring patterns in movie review sentiment and its correlations with movie attributes.
- Machine Learning Practitioners: To build, train, and test models for sentiment prediction and text classification, suitable for both beginners and intermediate users.
Dataset Name Suggestions
- Rotten Tomatoes Movie Review Sentiment Dataset
- Film Review Sentiment Analysis Data
- Movie Review NLP Dataset
- Rotten Tomatoes Text Reviews for Sentiment
Attributes
Original Data Source: Rotten Tomatoes Reviews
QUALITY