A MADOC (Reddit, fatpeoplehate) dataset of 1,409,008 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.
A Reddit (r/teaching community) dataset of 1,304,575 comments from r/teaching with 5-class sentiment scores, pre/post COVID labels (438,027 pre, 866,548 post), and relational language detection, collected by Cai et al. via Reddit API (2024). Each record contains comment text, post title, post selftext, created_utc, score, reply_count, pandemic_period (0=pre/1=post COVID), predicted_rating (1-5), normalized_sentiment (-1 to +1), contains_relational_word, sentiment_probabilities. 1,304,575 r/teaching comments with fine-grained 5-class sentiment analysis spanning pre/post COVID — enabling longitudinal study of how teaching community discourse and emotional tone shifted during the pandemic. Suitable for community sentiment analysis, COVID-19 discourse shifts, longitudinal NLP, education community research, relational language detection, sentiment classification.
A MADOC (Reddit, milliondollarextreme) dataset of 19,187 users and 422,964 reply edges from 1,286,148 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.
A Reddit (Pushshift archive, 2009-08) dataset of 1,226,620 comments and 566,453 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 1,521 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2009-08 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 1,521 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.
A Twitter (#NoMore hashtag campaign) dataset of 1,048,574 tweets from the Ethiopian #NoMore movement (2021-11 to 2022-08), collected by Zenodo contributors via Twitter API. Each record contains tweet text, language, timestamp; Amharic+English bilingual subset also available. 1,048,574 tweets covering the #NoMore solidarity movement in Ethiopia and Eritrea — one of few African social movement datasets with Amharic content, spanning 2021-11 to 2022-08. Suitable for African social movement analysis, multilingual NLP, Amharic text processing, political communication research, hashtag activism, Global South social media studies.
A Reddit (Pushshift archive, 2009-07) dataset of 1,043,399 comments and 483,183 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 1,463 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2009-07 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 1,463 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.
A MADOC (Reddit, greatawakening) dataset of 18,267 users and 302,678 reply edges from 915,265 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.
A Reddit (Pushshift archive, 2009-06) dataset of 905,351 comments and 415,296 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 1,303 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2009-06 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 1,303 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.
A Reddit (Pushshift archive, 2009-05) dataset of 501,150 comments and 386,262 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains directed reply graph, 1,207 subreddits, content metrics: score, controversiality, gilded. Monthly slice of the Pushshift Reddit corpus for 2009-05 — full comment text, reply graph, and engagement metrics across 1,207 subreddits.. Suitable for longitudinal Reddit analysis, reply network structure, community detection, sentiment analysis, engagement research.
A Reddit (Pushshift archive, 2009-04) dataset of 756,994 comments and 343,006 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 1,147 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2009-04 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 1,147 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.
A Reddit (Pushshift archive, 2009-03) dataset of 724,884 comments and 324,106 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 1,038 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2009-03 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 1,038 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.
A Reddit (Pushshift archive, 2009-01) dataset of 408,857 comments and 315,181 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains directed reply graph, 1,087 subreddits, content metrics: score, controversiality, gilded. Monthly slice of the Pushshift Reddit corpus for 2009-01 — full comment text, reply graph, and engagement metrics across 1,087 subreddits.. Suitable for longitudinal Reddit analysis, reply network structure, community detection, sentiment analysis, engagement research.
A Reddit (Pushshift archive, 2009-02) dataset of 646,978 comments and 287,037 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 972 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2009-02 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 972 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.
A Fitocracy dataset of 318,535 posts, 318,535 responses, collected by Peixian and Zhang. Each record contains posts, responses, op_gender, responder_gender, sentiment, relevance. rtGender dataset for Fitocracy — studies gendered responses in online discourse. Suitable for gender studies, sentiment analysis, response prediction.
A Reddit (Pushshift archive, full year 2007) dataset of 573,728 comments across 3 months, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains 35 subreddits, 357,430 reply edges across all months. Annual aggregate of all Pushshift Reddit comments for 2007 — 573,728 comments across 3 months and 35 subreddits.. Suitable for longitudinal Reddit analysis, annual growth trends, subreddit evolution, platform-scale engagement research.
A Reddit (Pushshift archive, 2008-12) dataset of 323,996 comments and 248,080 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains directed reply graph, 929 subreddits, content metrics: score, controversiality, gilded. Monthly slice of the Pushshift Reddit corpus for 2008-12 — full comment text, reply graph, and engagement metrics across 929 subreddits.. Suitable for longitudinal Reddit analysis, reply network structure, community detection, sentiment analysis, engagement research.
A Reddit (Pushshift archive, 2008-10) dataset of 303,507 comments and 230,724 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains directed reply graph, 698 subreddits, content metrics: score, controversiality, gilded. Monthly slice of the Pushshift Reddit corpus for 2008-10 — full comment text, reply graph, and engagement metrics across 698 subreddits.. Suitable for longitudinal Reddit analysis, reply network structure, community detection, sentiment analysis, engagement research.
A Reddit (Pushshift archive, 2008-11) dataset of 303,301 comments and 231,181 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains directed reply graph, 825 subreddits, content metrics: score, controversiality, gilded. Monthly slice of the Pushshift Reddit corpus for 2008-11 — full comment text, reply graph, and engagement metrics across 825 subreddits.. Suitable for longitudinal Reddit analysis, reply network structure, community detection, sentiment analysis, engagement research.
A Twitter dataset of 1,600,000 tweets with binary sentiment labels (positive/negative) assigned via emoticon distant supervision, collected by Go, Bhayani and Huang at Stanford University via Twitter streaming API in 2009. Each record contains tweet text with polarity label (0=negative, 4=positive), tweet ID, timestamp, search query used for collection, and username. The dataset is notable for its one of the largest and most widely used Twitter sentiment benchmarks, notable for using emoticons as a noisy but scalable distant supervision signal rather than manual annotation, enabling 1.6M labeled examples. Intended for research into sentiment analysis, opinion mining, distant supervision research, text classification benchmarking, and social media language modeling.
A Reddit (Pushshift archive, 2008-09) dataset of 261,881 comments and 199,295 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains directed reply graph, 665 subreddits, content metrics: score, controversiality, gilded. Monthly slice of the Pushshift Reddit corpus for 2008-09 — full comment text, reply graph, and engagement metrics across 665 subreddits.. Suitable for longitudinal Reddit analysis, reply network structure, community detection, sentiment analysis, engagement research.
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 Reddit (Pushshift archive, 2008-08) dataset of 397,916 comments and 174,362 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 583 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2008-08 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 583 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.
A Reddit (Pushshift archive, 2008-07) dataset of 390,922 comments and 172,692 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 548 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2008-07 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 548 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.
A Reddit (Pushshift archive, 2008-06) dataset of 387,630 comments and 173,588 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 431 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2008-06 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 431 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.
A Reddit (Pushshift archive, 2008-05) dataset of 218,148 comments and 167,545 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains directed reply graph, 287 subreddits, content metrics: score, controversiality, gilded. Monthly slice of the Pushshift Reddit corpus for 2008-05 — full comment text, reply graph, and engagement metrics across 287 subreddits.. Suitable for longitudinal Reddit analysis, reply network structure, community detection, sentiment analysis, engagement research.
A MADOC (Voat, fatpeoplehate) dataset of 20,942 users and 226,749 reply edges from 352,003 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.
A MADOC (Voat, greatawakening) dataset of 11,863 users and 155,890 reply edges from 324,835 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.
A Reddit (Pushshift archive, 2008-03) dataset of 187,499 comments and 143,043 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains directed reply graph, 259 subreddits, content metrics: score, controversiality, gilded. Monthly slice of the Pushshift Reddit corpus for 2008-03 — full comment text, reply graph, and engagement metrics across 259 subreddits.. Suitable for longitudinal Reddit analysis, reply network structure, community detection, sentiment analysis, engagement research.
A Reddit (Pushshift archive, 2008-04) dataset of 190,522 comments and 146,397 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains directed reply graph, 263 subreddits, content metrics: score, controversiality, gilded. Monthly slice of the Pushshift Reddit corpus for 2008-04 — full comment text, reply graph, and engagement metrics across 263 subreddits.. Suitable for longitudinal Reddit analysis, reply network structure, community detection, sentiment analysis, engagement research.
A Reddit (Pushshift archive, 2008-01) dataset of 315,422 comments and 147,025 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 117 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2008-01 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 117 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.
A Reddit (Pushshift archive, 2008-02) dataset of 305,452 comments and 139,599 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 156 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2008-02 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 156 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.
A Twitter dataset of 263,555 tweets with binary event labels (14,129 disruptive events, 248,499 non-events) related to Bitcoin and cryptocurrency markets, collected by Mehta et al. via Twitter API, 2021. Each record contains tweet text, binary event/non-event label, follower count, location, username, Bitcoin price at time of tweet, and retweet count. one of few datasets explicitly linking social media content to financial market disruption events, with synchronized Bitcoin price data enabling direct study of social signal → market movement relationships. Suitable for event detection, financial market prediction from social media, cryptocurrency sentiment analysis, and disruptive event classification.
A Reddit (Pushshift archive, 2007-12) dataset of 255,439 comments and 120,465 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 29 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2007-12 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 29 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.
A Reddit (Pushshift archive, 2007-11) dataset of 215,657 comments and 98,694 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 30 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2007-11 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 30 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.
A TikTok dataset of 209,543 videos from 1,872 creators, collected by Lingbo et al.. Each record contains video_id, author_id, create_time, description, transcript, GPT summary, topic, emotion scores, music metadata. Large-scale TikTok dataset with video metadata, GPT-generated summaries, emotion scores, and 30-day engagement trajectories. Suitable for engagement analysis, creator behavior, viral prediction, social media dynamics.
A TED dataset of 0 posts, 190,414 responses, collected by Peixian and Zhang. Each record contains posts, responses, op_gender, responder_gender, sentiment, relevance. rtGender dataset for TED — studies gendered responses in online discourse. Suitable for gender studies, sentiment analysis, response prediction.
Synthetic data: 150,000 generated social-media posts about Nigerian telecom operators (MTN, Airtel, Glo, 9mobile), published on Hugging Face by THUgewu as 'africa-synth'. The posts are not real user content. The file groups them into 978 rows by platform, operator, city and sentiment, with one list per field (post ID, time, text, issue category, likes, shares, comments, reach, sentiment score, operator response). Suitable for testing sentiment and customer-service pipelines, not for studying real users.
A MADOC (Voat, funny) dataset of 17,128 users and 82,319 reply edges from 143,945 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.
A Reddit (r/funny, r/pics, r/gifs and other popular subreddits) dataset of 132,214 Reddit posts across 837 subreddits with full comment threads, collected by Web scraper collecting top Reddit posts circa 2012. Each record contains post ID, subreddit, post title, upvotes, downvotes, submission timestamp, and full comment text for each thread. Complete HTML snapshots of 132,214 Reddit threads from ~2012, preserving the full discussion including post content, comment trees, and engagement metrics across 837 subreddits.. Suitable for community detection, Reddit discussion analysis, social engagement modeling, comment thread structure, subreddit community behavior.
A LiveJournal social network of 106,577 users and 961,392 directed edges (793,948 follower links and 246,164 friendship links), from a crawl of the users within three hops of the seed user krazykitkat, pre-processed for the paper 'Emotions in Social Networks: Distributions, Patterns, and Models' (Jin and Zafarani): only users with 10 or more posts carrying a predefined LiveJournal mood were kept, and user ids are anonymized. This copy holds the two network files (Friendship.txt, Followers.txt) and the release README; the per-post mood file (Posts.txt) and community memberships (Community.txt) that the README describes are not included. Suitable for social network structure, follower and friendship analysis, community detection, social influence modeling.
A Reddit (Pushshift archive, 2007-10) dataset of 59,814 comments and 46,281 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains directed reply graph, 32 subreddits, content metrics: score, controversiality, gilded. Monthly slice of the Pushshift Reddit corpus for 2007-10 — full comment text, reply graph, and engagement metrics across 32 subreddits.. Suitable for longitudinal Reddit analysis, reply network structure, community detection, sentiment analysis, engagement research.
A MADOC (Voat, videos) dataset of 10,756 users and 31,132 reply edges from 85,197 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.
A MADOC (Voat, technology) dataset of 14,397 users and 41,519 reply edges from 83,185 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.
A Jester Online Joke Recommender System (UC Berkeley) dataset of 73,521 nodes and 4,136,360 edges, collected by K. Goldberg et al. via Jester system. Each record contains directed: False, weighted: True, temporal: False. Bipartite user-joke rating network with continuous ratings from -10 to +10 — one of the earliest large-scale collaborative filtering datasets.. Suitable for recommender systems, collaborative filtering, continuous rating prediction.
A MADOC (Voat, gaming) dataset of 9,794 users and 28,073 reply edges from 69,478 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.
A Twitter (Nigerian language communities) dataset of 60,823 tweet IDs across 4 Nigerian languages with sentiment labels, collected by Muhammad et al. via Twitter API (2022). Each record contains tweet ID, sentiment label (positive/negative/neutral), language, split (train/dev/test). First large-scale sentiment corpus for Nigerian languages — 60,823 annotated tweet IDs across Hausa, Igbo, Yoruba, and Nigerian Pidgin, enabling low-resource African NLP research.. Suitable for low-resource NLP, African language sentiment analysis, multilingual classification, cross-lingual transfer..
A Reddit dataset of 54,075 subreddits and 571,927 directed hyperlinks (510,787 positive sentiment, 61,140 negative sentiment) from post hyperlinks embedded in post titles, collected by Kumar et al. via Reddit API, January 2014 to April 2017, distributed by SNAP. Each record contains directed edges from source to target subreddit with binary sentiment label (+1/-1) and 86-dimension text property vector; post ID and timestamp per edge. captures cross-community interaction and conflict on Reddit with sentiment polarity per hyperlink, enabling study of how communities reference each other positively vs. antagonistically over time. Suitable for community conflict detection, cross-community interaction modeling, signed network analysis, temporal network analysis, and online community dynamics research.
A SkyTrax dataset of 41,396 airline reviews from 362 airlines, collected by quankiquanki via SkyTrax (2014-2020). Each record contains review text, airline name, traveller type, cabin flown, overall rating, seat comfort, cabin staff, food and beverages, inflight entertainment, ground service, WiFi, value for money, and recommendation status. A comprehensive collection of airline reviews with detailed sub-ratings across multiple service dimensions, enabling granular sentiment analysis and service quality research. Suitable for sentiment analysis, service quality prediction, recommendation systems, customer satisfaction research.
A MADOC (Voat, pics) dataset of 7,712 users and 18,229 reply edges from 38,555 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.
A MySpace dataset of 80,749 messages between 36,459 users (41,533 directed user pairs) over two months, collected by Šuvakov et al. (Dryad, 2013). Each record holds the sender, the recipient, the time in minutes since the start of the window, and the message's SentiStrength positive (1 to 5) and negative (-1 to -5) scores. Suitable for sentiment dynamics, dialogue patterns and temporal network analysis.
Reddit
Twitter (X)
Fitocracy
Voat
TikTok
YouTube
Facebook
Instagram
LiveJournal
Skytrax
Myspace