11 datasets tagged as the topic “Sports”.
11 datasets.
A Reddit dataset of 398,487 comments from NFL subreddits during the 2020 draft, collected by Caio Brighenti via Reddit API (PRAW). Each record contains comment body, team, timestamp, VADER sentiment score, author. A real-time snapshot of NFL fan sentiment during the 2020 draft, capturing reactions to each pick across team subreddits. Suitable for sentiment analysis, sports analytics, social media analysis, fan behavior, natural language processing.
A Twitter (Moscow Athletics 2013) dataset of 88,804 users, 210,250 multiplex edges (retweets, mentions, replies), collected by D. R. G. and D. M.. Each record contains source, target, weight, layer (1=retweet, 2=mention, 3=reply). Multiplex Twitter network during Moscow Athletics 2013 with three interaction layers. Suitable for multiplex network analysis, event dynamics, information propagation.
A Amazon dataset of 146,891 QA pairs in Sports & Outdoors, collected by Wan and McAuley via Amazon API. Each record contains question, answer, question type, answer type, ASIN, timestamp. Amazon product Q&A data for Sports & Outdoors. Suitable for question answering, sentiment analysis, product understanding, conversational AI.
A Stack Exchange (sports.stackexchange.com) dataset of 4,209 users, 7,047 answer-collaboration edges, 6,107 questions, 9,016 answers, collected by Stack Exchange, Inc. via the annual Stack Exchange Data Dump. Each record contains user nodes (reputation, badge counts, vote history), directed weighted edges (answerer→asker, weight=answer score, count=interactions, accepted=bool), post text, tag distribution. User collaboration network from sports.stackexchange.com — directed weighted graph where edges represent knowledge-sharing relationships (A answered B's question), with edge weight reflecting answer quality. Enables prestige hierarchy, community detection, and expertise flow analysis.. Suitable for expertise network analysis, reputation systems, community detection, knowledge flow, PageRank-based authority ranking, Q&A platform dynamics..
A Stack Exchange (martialarts.stackexchange.com) dataset of 2,074 users, 5,256 answer-collaboration edges, 2,307 questions, 6,874 answers, collected by Stack Exchange, Inc. via the annual Stack Exchange Data Dump. Each record contains user nodes (reputation, badge counts, vote history), directed weighted edges (answerer→asker, weight=answer score, count=interactions, accepted=bool), post text, tag distribution. User collaboration network from martialarts.stackexchange.com — directed weighted graph where edges represent knowledge-sharing relationships (A answered B's question), with edge weight reflecting answer quality. Enables prestige hierarchy, community detection, and expertise flow analysis.. Suitable for expertise network analysis, reputation systems, community detection, knowledge flow, PageRank-based authority ranking, Q&A platform dynamics..
A Facebook dataset of 13,866 pages, 86,858 mutual likes, collected by Rozemberczki et al. via the Facebook Graph API (November 2017). Each record contains undirected edges between blue verified Facebook sport pages that mutually liked each other, with node attributes including page name and raw Facebook ID. Graph of blue verified Facebook sport pages, where edges represent mutual likes between pages, capturing how fans engage with sports teams, athletes, and sporting content. Suitable for community detection in social networks, graph embedding, sports fan engagement analysis, team rivalry studies, sports media and fandom network analysis.
A Voat (Reddit alternative, 2013–2020) dataset of 1,752 submissions, 7,296 comments, 1,070 users, 2,726 collaboration edges, collected by Mekacher & Papasavva (ICWSM 2022) via full platform crawl. Each record contains user nodes (registration date, moderation status), directed weighted edges (commenter→submitter, weight=upvotes+1), submission titles and bodies, comment text, upvotes, downvotes, depth. Complete dataset for the Voat subverse v/NFL, covering its full lifetime on the platform (2013–2020). Includes all 1,752 submissions and 7,296 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.
A Voat (Reddit alternative, 2013–2020) dataset of 2,294 submissions, 5,694 comments, 2,606 users, 3,666 collaboration edges, collected by Mekacher & Papasavva (ICWSM 2022) via full platform crawl. Each record contains user nodes (registration date, moderation status), directed weighted edges (commenter→submitter, weight=upvotes+1), submission titles and bodies, comment text, upvotes, downvotes, depth. Complete dataset for the Voat subverse v/sports, covering its full lifetime on the platform (2013–2020). Includes all 2,294 submissions and 5,694 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.
A Chess game records (professional matches) dataset of 7,301 nodes and 60,046 edges, collected by KONECT via chess game database. Each record contains directed: True, weighted: True, signed: True. Directed network of chess game outcomes: edges go from winner to loser, with timestamps. Draws encoded as 0 weight.. Suitable for competition network analysis, ranking algorithms, temporal network analysis.
A Twitter dataset of 5,171 sentiment-labeled tweets about NFL teams, collected by Cameron C (Kaggle user cammyc) via Twitter API. Each record contains tweet text, sentiment (positive/negative/neutral), team, username, timestamp, confidence score. A curated dataset of 3,701 NFL-related tweets with sentiment labels, enabling research on sports fan sentiment, team-specific public opinion, and social media engagement patterns during the NFL season. Suitable for sentiment analysis, sports marketing, fan engagement, public opinion tracking, temporal sentiment analysis.
A Reddit dataset of 365 posts about Bundesliga football teams, collected by Reddit Data Archive via Reddit API. Each record contains post content, votes (score), comment count, team label, date, author. Small dataset of Reddit posts about Bundesliga football teams, capturing fan discussions and engagement across multiple clubs.. Suitable for sports analytics, sentiment analysis, fan community dynamics, engagement prediction.
Reddit
Twitter (X)
Amazon
Stack Exchange
Facebook
Voat