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Premier League Fan Engagement Dataset
Social Media and Networking
Tags and Keywords
Trusted By
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Free
About
This dataset provides insights into online discussions surrounding Fantasy Premier League (FPL), a widely popular online fantasy football game based on the English Premier League. FPL allows participants to select real-life Premier League players and earn points based on their actual match performances. The game boasts over 9 million registered users globally, making it a prominent fantasy sports platform. For context, an FPL team typically operates with a budget of £100.0m, and top players like Mohamed Salah have achieved significant scores, with Salah holding the record for 303 points in the 2017/18 season. This collection of tweets, specifically containing keywords such as "Fantasy Premier League" and "FPL", was gathered using the snscrape library. It offers a valuable resource for understanding the FPL community, gauging interest levels, and analysing player experiences through social media chatter.
Columns
- ID: A unique identifier assigned to each tweet.
- Timestamp: The precise date and time when the tweet was originally posted.
- User: The username of the individual who posted the tweet.
- Text: The actual content or message of the tweet.
- Hashtag: Any hashtags that were included within the tweet's content.
- Retweets: The total number of times the tweet had been retweeted when the data was collected.
- Likes: The total number of likes the tweet had received when the data was collected.
- Replies: The total number of replies directed at the tweet when the data was collected.
- Source: The specific application or device used by the user to post the tweet, such as "Twitter for Android" or "Twitter for iPhone".
- Location: The geographical location optionally specified on the user's Twitter profile.
- Verified_Account: A true or false value indicating whether the user's Twitter account was verified at the time of scraping.
- Followers: The count of followers the user had when the tweet data was scraped.
- Following: The count of accounts the user was following when the tweet data was scraped.
Distribution
The dataset contains 114,466 tweets. The data is typically available in a CSV file format. It encompasses a substantial number of unique users, with 112,217 distinct user accounts represented. Additionally, there are 54,030 unique location values captured from user profiles. A breakdown of tweet sources indicates that 19% originate from "Twitter for Android", 17% from "Twitter for iPhone", and 65% from other sources. A notable portion (29%) of source information is null. For hashtags, 75% are null, 4% include 'FPL', and 21% represent other hashtags. The majority of tweets (114,394) have between 0 and 156 retweets, while 114,352 tweets have between 0 and 1,719 likes. Similarly, 114,168 tweets have between 0 and 26 replies. The maximum recorded retweets for a single tweet is 7,805, while the maximum likes is approximately 86,000, and the maximum replies is 1,317.
Usage
This dataset is well-suited for various analytical tasks, particularly in the fields of natural language processing (NLP) and machine learning. Ideal applications include:
- Sentiment analysis: Determining the overall mood or emotional tone of tweets related to FPL.
- Topic modelling: Identifying key themes and subjects discussed within the FPL community on Twitter.
- Community analysis: Gaining insights into the dynamics and interests of FPL players and enthusiasts.
- Interest assessment: Measuring the level of online engagement and popularity of FPL over time.
- User experience studies: Understanding the challenges, successes, and general experiences of playing FPL as expressed by users.
Coverage
The dataset spans tweets collected from 2012 to 2023, specifically between 29 October 2012 and 9 April 2023. Geographically, the data reflects a global scope, consistent with FPL's worldwide user base of over 9 million registered users. The collection process aimed to gather a substantial number of tweets for each year within this period.
License
CCO
Who Can Use It
- Data Scientists and Machine Learning Engineers for developing NLP models and predictive analytics.
- Market Researchers and Brand Strategists interested in social media trends and community engagement in the sports sector.
- Academics and Students for research projects on social media analytics, fan behaviour, or fantasy sports.
- Sports Analysts and Fantasy Sports Enthusiasts looking to understand FPL discourse and sentiment.
Dataset Name Suggestions
- FPL Tweets Data 2012-2023
- Fantasy Premier League Twitter Archive
- Premier League Fan Engagement Dataset
- Social Media Chatter on FPL
Attributes
Original Data Source: FPL Tweets Dataset
QUALITY