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Harry Potter Reader Reviews
Entertainment & Media Consumption
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset contains reviews and related metrics for books, with a particular focus on the globally popular Harry Potter series. The series, by British author J. K. Rowling, chronicles the adventures of young wizard Harry Potter and his friends at Hogwarts School of Witchcraft and Wizardry, as they confront Lord Voldemort. The books have achieved remarkable popularity and commercial success worldwide, selling over 500 million copies and translated into numerous languages. The franchise's overall value was estimated at $25 billion in 2016, highlighting its cultural and economic impact. This dataset offers insights into reader feedback, engagement patterns, and the reception of one of the best-selling book series in history.
Columns
id: A unique identifier for each review.book: The title of the book being reviewed.title: The title of the review itself.name: The name of the reviewer.username: The username of the reviewer.date: The date when the review was published.rating: A numerical rating given by the reviewer.likes: The total number of likes the review received.description: The textual content of the review.stars_given: The number of stars awarded by the reviewer.
Distribution
The dataset is typically provided in a CSV format, with a sample file available on the platform. While specific numbers for rows are not explicitly stated, the data appears to consist of approximately 719 individual reviews.
Key distributions within the dataset include:
- Ratings: Most reviews are highly positive, with 468 entries giving 4.60-5.00 stars. Other significant ranges include 3.80-4.20 stars (118 entries), 3.00-3.40 stars (46 entries), 1.00-1.40 stars (32 entries), and 1.80-2.20 stars (26 entries).
- Review Descriptions: Many descriptions are positive, with "itwasamazing" accounting for 65% of entries and "reallylikedit" for 16%. The remaining 19% falls into other categories.
- Reviewer Activity: A small number of usernames, such as 'Jayson' and 'Luffy', each contribute 2% of the reviews, with the vast majority (96%) coming from other users.
- Likes: A small percentage of reviews received 70 likes (2%) or 84 likes (2%), with 97% of reviews falling into other like counts.
Usage
This dataset is well-suited for a variety of applications, including:
- Sentiment Analysis: Analysing the emotional tone and opinions expressed in book reviews.
- Natural Language Processing (NLP): Developing and testing NLP models for text classification, entity recognition, or topic modelling on review content.
- Market Research: Understanding reader preferences, identifying popular book titles, and assessing the impact of a globally recognised book series.
- Reader Engagement Studies: Examining trends in review activity, reviewer behaviour, and the types of reviews that receive more engagement (likes).
- Recommendation Systems: Informing the development of systems that suggest books to readers based on review data.
Coverage
- Geographic Scope: The reviews are global in nature, reflecting the worldwide popularity of the Harry Potter series.
- Time Range: The reviews span a considerable period, from February 2007 to December 2021. Review counts peaked between January 2016 and June 2017 (204 reviews), with other active periods including January 2013 to July 2014 (86 reviews) and August 2011 to January 2013 (63 reviews).
- Demographic Scope: The reviews originate from readers who engage with the Harry Potter book series, which has attracted a wide audience encompassing both younger readers and adults.
License
CC0
Who Can Use It
- Data Analysts and Scientists: For projects involving text analysis, sentiment modelling, and understanding consumer feedback.
- Academics and Researchers: Studying literature, media consumption, and the impact of popular cultural phenomena.
- Publishing Industry Professionals: Gaining insights into reader reception, informing marketing strategies, and identifying trends in literary reviews.
- Content Creators and Marketers: For understanding audience engagement with popular media and tailoring content.
Dataset Name Suggestions
- Harry Potter Reader Reviews
- Global Book Review Analytics
- Fantasy Novel Consumer Feedback
- Literary Ratings Dataset
- Book Series Engagement Data
Attributes
Original Data Source: Harry Potter Reviews
QUALITY