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MyAnimeList Top Anime Metrics
Product Reviews & Feedback
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"No reviews yet"
Free
About
Provides detailed information about the top 10,000 Anime entries, alongside 85,000 user reviews and 45,000 user recommendations sourced from the MyAnimeList (MAL) platform. This resource offers key data attributes such as anime ranking, score, and genre, enabling analysis of factors influencing an anime's success and popularity. MyAnimeList is a prominent social cataloguing website utilised globally by fans of anime and manga.
Columns
The dataset contains information across multiple files, with the recommendations sample featuring five core columns:
- Rank: The numerical ranking position of the anime.
- Anime Title: The official title of the anime entry.
- Anime URL: The specific recommendation URL associated with the main anime entry.
- Recommended Title: The title of the specific anime being suggested by users as a recommendation.
- No. of Recommendations: The tally of users who have recommended this particular title.
Distribution
The data is usually provided in the standard CSV file format. The specific sample file detailing user recommendations includes five columns and contains approximately 45,400 records.
Usage
This resource is ideal for developing robust recommender models tailored for anime content. It can also be applied to exploratory data analysis regarding user engagement and sentiment, and for researching the underlying mechanisms that drive the popularity and user ranking of animation titles. Additionally, the associated review data can be used to build classification or sentiment analysis algorithms.
Coverage
The data reflects information scraped up to 15 October 2020, focusing on the top 10,000 anime titles listed on the MyAnimeList platform. Coverage is global, reflecting the activity and ratings of the international user community (often referred to as Otakus).
License
CC0: Public Domain
Who Can Use It
- Data Scientists developing machine learning models, particularly focusing on recommendation systems or natural language processing (NLP) tasks related to user reviews.
- Academics and researchers conducting studies into media popularity, viewer metrics, and online social cataloguing.
- Data analysts performing exploratory analysis on entertainment content ratings, genres, and community engagement.
Dataset Name Suggestions
- MyAnimeList Top Anime Metrics
- MAL 10K Anime and User Recommendations
- Anime Popularity and Review Data (2020)
Attributes
Original Data Source: MyAnimeList Top Anime Metrics
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