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Small-Scale Movie Review Sentiment Data
Product Reviews & Feedback
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"No reviews yet"
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About
Movie reviews from IMDB facilitate a deep exploration of audience sentiment and critical reception. These entries capture qualitative feedback on cinematic productions, enabling the identification of linguistic patterns and emotional undertones. By recording reviewer identities and publication dates, the material supports studies on how film reception shifts over time and across different professional perspectives. It serves as a vital resource for training machine learning models to interpret human opinion and nuances in language.
Columns
- Name: Identifies the individual reviewer responsible for the critique; professional critics such as Tim Goodman are represented within the records.
- Reviews: The core textual content containing the movie critique, providing the basis for sentiment analysis and linguistic modelling.
- Date: The specific day the review was submitted, recorded in a date-time format for chronological analysis.
Distribution
The information is delivered in a CSV format titled
Small Reviews.csv, which has a file size of 9.88 kB. The collection consists of 3 columns and contains 47 unique records. It maintains a high usability rating of 10.00 and is expected to be updated on a quarterly basis.Usage
This resource is ideal for training algorithms focused on sentiment analysis and next-word prediction. It can be applied in the development of chatbots, language translation tools, and text classification systems. Researchers can also utilise the data for exploratory data analysis and text mining to uncover trends in film criticism.
Coverage
The temporal scope is focused on a specific period in 2013, with reviews dated between 14th June and 25th July. The demographic reach includes various reviewers contributing to the IMDB platform, capturing a snapshot of cinematic discussion during that timeframe.
License
CC0: Public Domain
Who Can Use It
Data scientists and machine learning engineers can use these reviews to build and test natural language processing models. Film historians and media analysts might employ the data to study audience reactions to 2013 cinema. Additionally, students can use the records as a manageable sample for practicing data cleaning and text classification techniques.
Dataset Name Suggestions
- IMDB Cinematic Sentiment and Review Corpus
- 2013 Summer Movie Review Collection
- Small-Scale Movie Review Sentiment Data
- IMDB Reviewer Feedback and Chronology
Attributes
Original Data Source: Small-Scale Movie Review Sentiment Data
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