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Cinematic Preferences and User Rating Index
Product Reviews & Feedback
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About
Exploring audience preferences through individual feedback provides the foundation for personalising the cinematic experience. This collection captures how different users perceive various films, categorising their tastes by genre and specific movie titles. By documenting numerical ratings on a standardised scale, the data helps reveal the intricate relationship between genre popularity and user satisfaction. Such insights are fundamental for developing algorithms that predict future viewing habits and enhance digital content discovery.
Columns
- User_ID: A unique numerical identifier assigned to each individual user providing ratings.
- Movie_ID: A unique numerical identifier for every specific film included in the record set.
- Movie_Name: The unique title of the film that has been reviewed by the user.
- Genre: The categorical classification of the movie, representing genres such as Drama, Comedy, Sci-Fi, Crime, Romance, Fantasy, Animation, Horror, Musical, Action, Adventure, and Thriller.
- Rating: A numerical value on a scale of 1 to 5 representing the user’s level of appreciation for the film, where 5 indicates the highest satisfaction.
Distribution
The information is delivered as a CSV file titled
movies.csv with a compact file size of approximately 2 kB. It consists of 62 valid records structured across 5 distinct columns. The data exhibits high integrity, with 100% validity across all entries and no reported missing or mismatched information. This resource is not expected to receive future updates.Usage
This resource is ideal for building and testing movie recommendation engines and collaborative filtering models. It is well-suited for conducting genre-based market analysis to identify which film types, such as Drama or Comedy, receive the highest average scores. Additionally, researchers can use the data to study user behaviour patterns and the distribution of ratings across a varied cinematic catalogue to understand preference trends.
Coverage
The scope includes ratings for 61 unique movie titles across 12 different genres, with Drama and Comedy being the most frequently represented categories. User identifiers range from 1 to 30, and the ratings recorded in this sample primarily fall between 2 and 5, with a mean score of 4.16. The demographic focus is centred on individual user interactions with a diverse array of films, from thrillers to musicals.
License
CC BY-SA 4.0
Who Can Use It
Data scientists can leverage these ratings to train predictive models for content personalisation and recommendation systems. Marketing analysts might utilise the genre classifications to understand audience trends and tailor promotional strategies for specific film categories. Furthermore, students of machine learning can find this a valuable primary source for practicing database management and recommendation algorithm development.
Dataset Name Suggestions
- Cinematic Preferences and User Rating Index
- Multi-Genre Movie Recommendation Schema
- User Feedback and Film Affinity Database
- Digital Cinema Recommendation Framework
- Personalised Movie Rating and Genre Analytics
Attributes
Original Data Source: Cinematic Preferences and User Rating Index
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