A twitter dataset of 2.7B+ tweet IDs across 9+ languages (ongoing collection since Jan 2020), collected by Chen, Lerman, and Ferrara (USC Information Sciences Institute). Each record contains tweet IDs only — full content requires hydration. Largest ongoing COVID-19 Twitter collection with multilingual coverage and continuous updates since pandemic onset. Suitable for pandemic discourse, public health surveillance, infodemic analysis, multilingual NLP.
A twitter dataset of 295,670,111 tweet IDs from the 2020 U.S. presidential election, collected by Wrubel and Kerchner via Social Feed Manager (GWU Libraries). Each record contains tweet IDs only — full content requires hydration. Complete tweet archive from the 2020 election including post-election period and January 6 lead-up. Suitable for election discourse, misinformation, political polarization, post-election unrest.
A twitter dataset of ~280 million tweet IDs from the 2016 U.S. presidential election period, collected by Littman, Wrubel, and Kerchner via Social Feed Manager (GWU Libraries). Each record contains tweet IDs only — full content requires hydration. One of the largest election tweet archives, covering the full 2016 campaign including debates, conventions, and election night. Suitable for election discourse, political polarization, misinformation spread, retweet diffusion.
A Reddit (Pushshift archive, full year 2012) dataset of 214,852,051 comments across 12 months, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains 55,276 subreddits, 126,092,201 reply edges across all months. Annual aggregate of all Pushshift Reddit comments for 2012 — 214,852,051 comments across 12 months and 55,276 subreddits.. Suitable for longitudinal Reddit analysis, annual growth trends, subreddit evolution, platform-scale engagement research.
A Reddit (Pushshift archive, full year 2011) dataset of 98,768,846 comments across 12 months, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains 24,979 subreddits, 56,715,997 reply edges across all months. Annual aggregate of all Pushshift Reddit comments for 2011 — 98,768,846 comments across 12 months and 24,979 subreddits.. Suitable for longitudinal Reddit analysis, annual growth trends, subreddit evolution, platform-scale engagement research.
A Foursquare dataset of 22,809,624 check-ins, 114,324 users, 3,820,891 venues, collected by Yang et al. via Foursquare API (2012–2014). Each record contains check-in timestamps, venue IDs, GPS coordinates, venue categories, friendship edges. One of the largest public Foursquare datasets with both check-in histories and social networks. Suitable for location-based social network analysis, user mobility, POI recommendation, community detection.
Twitter History and Image Sharing (THIS) v1.0: country-level aggregates of about 14.6 billion geolocated tweets, 2013 to 2023, released by Zachary Steinert-Threlkeld on Harvard Dataverse. Four tables, 17,928,584 rows in all: tweets and users per country and day (792,313 rows), tweets per country, language and day (15,407,849), new accounts per country and day (943,361), and image-sharing availability per country and day (785,061). No individual tweets or users are included. Suitable for country-level trends in platform use, language use and image sharing.
A Reddit (Pushshift archive, full year 2008) dataset of 4,873,571 comments across 12 months, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains 2,181 subreddits, 2,955,005 reply edges across all months. Annual aggregate of all Pushshift Reddit comments for 2008 — 4,873,571 comments across 12 months and 2,181 subreddits.. Suitable for longitudinal Reddit analysis, annual growth trends, subreddit evolution, platform-scale engagement research.
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 TikTok dataset of 1,035,817 videos, 4,920 creators, 27,169,858 engagement records, collected by Lingbo et al.. Each record contains video_id, author_id, create_time, description, hashtags, music, daily engagement (plays, likes, comments, shares, collects). Large-scale TikTok dataset with video metadata and 30-day engagement trajectories. Suitable for engagement analysis, creator behavior, viral prediction, social media dynamics.
A twitter dataset of 690,281 tweet IDs from state health agencies, CDC, and FDA (2012–2022), collected by Mendez via academictwitteR (Harvard Dataverse, 2023). Each record contains tweet IDs, account state/agency labels — full content requires hydration. Longitudinal institutional public health Twitter archive spanning pre-pandemic baseline through COVID-19 response. Suitable for public health communication, pandemic response analysis, institutional messaging.
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 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 dataset of 255,363 tweet IDs about the 2022 monkeypox outbreak, collected by Thakur (University of Cincinnati, 2022). Each record contains tweet IDs only — full content requires hydration. First public Twitter dataset on the 2022 monkeypox outbreak, enabling early-stage disease discourse analysis. Suitable for disease surveillance, public health communication, health misinformation.
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 Gnutella peer-to-peer network dataset combining the 9 SNAP snapshots of August 2002 (Ripeanu et al.): 191,327 nodes and 506,442 directed edges in all. SNAP numbers the hosts of each snapshot separately, so the snapshots sit side by side in one graph with node IDs of the form snapshot:host, and no host is linked across snapshots. Suitable for temporal network analysis, graph evolution, and peer-to-peer network resilience.
A Meneame dataset of 14,995 articles, 20,000 comments, 45,392 users, collected by Meneame Media Bias Team. Each record contains article title, text, bias labels, sentiment, emotion scores, karma features, user-outlet graph. Spanish social news aggregator dataset with media bias labels and rich interaction features. Suitable for media bias detection, sentiment analysis, social news dynamics, graph analysis.
A Twitter (aggregate) dataset of 4,709,404 topic-related tweets across 6 social issues, collected by NORC at the University of Chicago. Each record contains date, topic, daily volume, VADER compound sentiment, pos/neg ratio, account type (community/bot/news/government/activist), US state. Aggregate Twitter data on six politically salient social issues with daily volume and VADER sentiment scores 2016-2022, including unique bot-vs-community account type breakdowns and US state-level marijuana discourse data. Suitable for political communication, sentiment trends, bot detection, state-level public opinion, longitudinal social issue analysis.
A World Bank dataset of 208 countries spanning 1990–2025, collected by World Bank via World Development Indicators. Each record contains country name, country code, internet usage percentage per year. Global internet penetration time-series from 1990 to 2025 covering over 200 countries with annual observations. Suitable for digital divide analysis, internet adoption trends, cross-country comparison, development economics.
A Twitter (English corpus, 2B+ tweets) dataset of 11 years of monthly n-gram frequency counts (2013-2023), collected by Zenodo contributors via Twitter corpus analysis. Each record contains n-gram text, n-gram type (1=unigram, 2=bigram, etc.), monthly frequency count; both case-sensitive and lowercase variants. Monthly n-gram frequency distributions from over 2 billion English tweets spanning 2013-2023, enabling longitudinal linguistic trend analysis on Twitter at scale. Suitable for longitudinal linguistic analysis, trending topic detection, language change over time, Twitter vocabulary evolution, NLP corpus statistics, temporal word frequency research.
A OECD dataset of 44 countries spanning 2008–2023, collected by OECD via Zenodo. Each record contains Country, year, indicator, observation value, breakdowns by age/gender/education. Detailed ICT usage data with demographic breakdowns. Suitable for digital divide analysis, ICT adoption trends.
A Twitter, Facebook, and Instagram dataset of 44 quarterly records spanning Q1 2010 to Q4 2020, collected by Margaretha Martinez via CNBC and Statista (2021). Each record contains quarter label, Twitter MAU (millions), Facebook MAU (millions), Instagram MAU (millions). A longitudinal quarterly time-series tracking monthly active user counts for three major social media platforms across a decade of growth. Suitable for platform growth analysis, social media market trends, digital media landscape studies, longitudinal comparison research.
A Pew Research Center dataset of 11 annual survey waves spanning 2012–2025, collected by Pew Research Center via annual US adult surveys. Each record contains survey year, platform-specific adoption percentages for US adults. Annual survey tracking US adult adoption rates across all major social media platforms from 2012 to the present. Suitable for social media adoption trends, platform popularity analysis, digital behavior research, longitudinal survey analysis.
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