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EA Football Game Player Feedback Data
Product Reviews & Feedback
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About
The data captures user reviews and interaction details for FIFA 23, a popular football video game franchise released annually by EA. EA is known for developing and publishing major video game franchises, while Steam is a leading platform for purchasing and playing games on personal computers. The FIFA game features licensed teams, players, and various game modes, including Ultimate Team. This collection provides insight into public reception and sentiment trends regarding the title shortly after its launch, containing over 25,000 user recommendations sourced from the Steam platform. Analysis of this material helps determine player satisfaction levels and behavioral patterns related to game ownership and playtime.
Columns
- id: The unique identification number assigned to the user recommendation.
- language: Specifies the language used in the review text; all included entries in this collection are in English.
- review: The actual text content written by the user.
- created: The exact date and time when the user submitted the review.
- voted_up: A Boolean flag indicating whether the reviewer recommended the game (True) or not (False). Approximately 55% of reviews fall into the 'True' category.
- votes_up: A count detailing how many other users upvoted the review as helpful or agreeable (maximum recorded is 1897).
- comment_count: The total number of comments left by other users on the original review post (maximum recorded is 72).
- steam_purchase: A Boolean marker showing if the game was acquired directly through the Steam platform (approximately 83% True).
- recieved_for_free: A Boolean marker indicating if the user obtained the game without paying (approximately 95% False).
- written_during_early_access: A Boolean flag indicating if the review was posted during the game's early availability period (all records show False).
- author_num_games_owned: The total count of video games the author owns on their Steam account (maximum recorded is 8221).
- author_num_reviews: The quantity of reviews previously submitted by the user (maximum recorded is 4310).
- author_playtime_forever: The author's total accumulated lifetime playtime for FIFA 23, measured in minutes (maximum recorded is 157,000 minutes).
- author_playtime_last_two_weeks: The author's playtime recorded during the two weeks prior to the data being collected (maximum recorded is 20,200 minutes).
- author_playtime_at_review: The author’s total playtime on the game, in minutes, at the moment the review was written (maximum recorded is 120,000 minutes).
- author_last_played: The date the user most recently engaged with the game.
Distribution
The data is structured in a tabular format, featuring 16 columns. It is distributed as a single CSV file, named
fifa23_steam_reviews.csv, and has a size of 5.43 MB. The collection contains over 25,000 valid records. The expected update frequency is 'Never', indicating that the dataset is static.Usage
This data product is perfectly suited for deep sentiment analysis using Natural Language Processing (NLP) techniques to extract meaningful feedback from user-generated text. It can be utilised to train machine learning models to classify positive and negative feedback regarding video game performance, features, or updates. Further analysis can explore patterns linking high player engagement metrics (such as accumulated playtime or ownership history) with the resulting feedback quality and sentiment.
Coverage
The reviews included span a time period from 29 September 2022 to 12 March 2023. The language scope is strictly focused on English-language reviews. The demographic scope includes PC gamers who use the Steam distribution platform and submitted a review for FIFA 23, capturing details on their activity both within the game and across the platform.
License
CC0: Public Domain
Who Can Use It
- Data Scientists: For developing and applying NLP techniques to mass quantities of user-generated text.
- Video Game Publishers and Developers: To gain direct, unfiltered feedback from their PC player base regarding game mechanics or specific modes like Ultimate Team.
- Market Researchers: Studying consumer reactions to high-profile entertainment software releases.
- Academics: Researching online rating systems, digital platform dynamics, and user engagement metrics.
Dataset Name Suggestions
- FIFA 23 Steam User Feedback and Engagement Data
- EA FIFA 23 PC Gamer Reviews (Sept 2022 - March 2023)
- Video Game Sentiment Analysis Dataset: FIFA 23
Attributes
Original Data Source: EA Football Game Player Feedback Data
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