A Deezer (Romania) dataset of 54,573 users, 498,202 friendships, collected by Rozemberczki et al. via Deezer music streaming service (November 2017). Each record contains undirected edges between Deezer users representing mutual friendships, with node attributes including genre preferences (84 distinct genres). Friendship network from Deezer music streaming service in Romania, with rich genre preference metadata enabling music-based community detection and user behavior analysis. Suitable for community detection, graph embedding, music preference analysis, social network analysis, recommendation systems.
A GitHub (user-repository starring/watching network) dataset of 177,386 nodes and 440,237 edges, collected by KONECT via GitHub API. Each record contains directed: False, weighted: False, temporal: False. Bipartite network of GitHub users and repositories — edges represent starring or watching relationships.. Suitable for open source collaboration analysis, bipartite network analysis, software ecosystem research.
A GitHub (stargazers network) dataset of 1,448,038 nodes and 2,985,781 edges across 12,725 graphs, collected by Rozemberczki et al. via GitHub API (2019). Each record contains graph ID, binary label (0=web development, 1=machine learning), developer-user follower edges. The dataset is notable for its graph classification dataset with 12,725 small graphs, each representing the social network of developers who starred a repository. Intended for research into graph classification, social network analysis, developer behavior modeling, and transfer learning.
A Gnutella (August 04, 2002) dataset of 10,876 nodes and 39,994 edges, collected by Ripeanu et al. via Gnutella crawl (2002). Each record contains directed peer-to-peer connections in the Gnutella network. The dataset is notable for its snapshot from August 04, 2002, part of a temporal sequence of 9 snapshots. Intended for research into peer-to-peer network analysis, temporal graph evolution, and network resilience studies.
A Gnutella (August 05, 2002) dataset of 8,846 nodes and 31,839 edges, collected by Ripeanu et al. via Gnutella crawl (2002). Each record contains directed peer-to-peer connections in the Gnutella network. The dataset is notable for its snapshot from August 05, 2002, part of a temporal sequence of 9 snapshots. Intended for research into peer-to-peer network analysis, temporal graph evolution, and network resilience studies.
A Gnutella (August 06, 2002) dataset of 8,717 nodes and 31,525 edges, collected by Ripeanu et al. via Gnutella crawl (2002). Each record contains directed peer-to-peer connections in the Gnutella network. The dataset is notable for its snapshot from August 06, 2002, part of a temporal sequence of 9 snapshots. Intended for research into peer-to-peer network analysis, temporal graph evolution, and network resilience studies.
A Gnutella (August 08, 2002) dataset of 6,301 nodes and 20,777 edges, collected by Ripeanu et al. via Gnutella crawl (2002). Each record contains directed peer-to-peer connections in the Gnutella network. The dataset is notable for its snapshot from August 08, 2002, part of a temporal sequence of 9 snapshots. Intended for research into peer-to-peer network analysis, temporal graph evolution, and network resilience studies.
A Gnutella (August 09, 2002) dataset of 8,114 nodes and 26,013 edges, collected by Ripeanu et al. via Gnutella crawl (2002). Each record contains directed peer-to-peer connections in the Gnutella network. The dataset is notable for its snapshot from August 09, 2002, part of a temporal sequence of 9 snapshots. Intended for research into peer-to-peer network analysis, temporal graph evolution, and network resilience studies.
A Gnutella (August 24, 2002) dataset of 26,518 nodes and 65,369 edges, collected by Ripeanu et al. via Gnutella crawl (2002). Each record contains directed peer-to-peer connections in the Gnutella network. The dataset is notable for its snapshot from August 24, 2002, part of a temporal sequence of 9 snapshots. Intended for research into peer-to-peer network analysis, temporal graph evolution, and network resilience studies.
A Gnutella (August 25, 2002) dataset of 22,687 nodes and 54,705 edges, collected by Ripeanu et al. via Gnutella crawl (2002). Each record contains directed peer-to-peer connections in the Gnutella network. The dataset is notable for its snapshot from August 25, 2002, part of a temporal sequence of 9 snapshots. Intended for research into peer-to-peer network analysis, temporal graph evolution, and network resilience studies.
A Gnutella (August 30, 2002) dataset of 36,682 nodes and 88,328 edges, collected by Ripeanu et al. via Gnutella crawl (2002). Each record contains directed peer-to-peer connections in the Gnutella network. The dataset is notable for its snapshot from August 30, 2002, part of a temporal sequence of 9 snapshots. Intended for research into peer-to-peer network analysis, temporal graph evolution, and network resilience studies.
A Gnutella (August 31, 2002) dataset of 62,586 nodes and 147,892 edges, collected by Ripeanu et al. via Gnutella crawl (2002). Each record contains directed peer-to-peer connections in the Gnutella network. The dataset is notable for its snapshot from August 31, 2002, part of a temporal sequence of 9 snapshots. Intended for research into peer-to-peer network analysis, temporal graph evolution, and network resilience studies.
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 Google+ dataset of 211,187 users, 1,506,896 circle memberships, collected by Fire et al. via Google+ API (2013). Each record contains directed edges between Google+ users representing circle memberships (user → circle). Google+ social graph capturing directed circle relationships, where users add others to their circles, creating a directed social graph structure. Suitable for link prediction, social network analysis, community detection, circle-based social behavior analysis.
A TREC web corpus dataset of 58,434 nodes and 978,446 edges, collected by T. Gottron et al.. Each record contains directed: False, weighted: True. Bipartite network of web documents and terms from the TREC web corpus.. Suitable for document-term network analysis, information retrieval, web graph research.
A Google Scholar dataset of 82,937 papers, 148,116 citations, collected by Google Scholar via academic citation data. Each record contains citation edges between papers, node IDs, node names (titles), node types (paper, author, etc.), edge types (cites, etc.). Academic citation network from Google Scholar, capturing the flow of scientific knowledge through citation relationships. Suitable for citation analysis, academic network analysis, research impact, knowledge flow studies, scholarly communication.
A Twitter (crowdsourced hate speech annotation) dataset of 24,783 tweets labeled as hate speech (1,430), offensive (19,190), or neither (4,163), collected by Davidson et al. via CrowdFlower crowdsourcing (2017). Each record contains tweet text, majority class label (0=hate/1=offensive/2=neither), per-label coder counts, total coder count. Davidson et al. 2017 is one of the most cited hate speech datasets, with 24,783 tweets annotated by multiple crowdworkers — distinguished by separating hate speech from merely offensive language. Suitable for hate speech detection, offensive language classification, content moderation, NLP benchmarking, crowdsourced annotation research.
A Twitter (hateful user network) dataset of 100,386 users (544 hateful, 4,427 normal, 0 suspended) with 2,286,592 follower edges, collected by Ribeiro et al. via Twitter API (2018). Each record contains user ID, hate label (hateful/normal/suspended), follower/followee/statuses counts, network centrality metrics, 200+ Empath emotional category scores, 300-dim GloVe embeddings, sentiment, subjectivity, tweet engagement statistics. One of the most feature-rich hateful user datasets, with 100,386 Twitter users labeled for hatefulness and supplemented with full network topology, Empath psychological features, and GloVe embeddings. Suitable for hate speech detection, hateful user classification, network-based toxicity analysis, suspended account detection, social influence of hate, graph-based hate propagation.
A Twitter dataset of 38,918 users and 32,523 directed, weighted reply edges (36,902 replies in all), collected by De Domenico et al. via the Twitter Streaming API around the Higgs boson announcement, 1-7 July 2012. Each record holds the replying user ID, the replied-to user ID and the number of replies between them. Complements the Higgs retweet and mention networks from the same collection. Suitable for information diffusion, scientific communication on social media and reply network structure.
A HOT Speech (hate/offensive/toxic speech dataset) dataset of 3,481 social media comments with multi-dimensional annotations, collected by SOMAR / ICPSR via Twitter, YouTube, and Reddit APIs (August 2021). Each record contains comment text, hard and soft labels (hateful, offensive, toxic), composite scores, and 21 researcher codes. multi-platform dataset with rich annotations including both MTurk worker labels and researcher codes. Suitable for hate speech detection, offensive language identification, toxicity classification, and political discourse analysis.
A Twitter dataset of 7,376 tweets from california_wildfires_2018, collected by Alam et al. for california_wildfires_2018 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the california_wildfires_2018 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 2,242 tweets from canada_wildfires_2016, collected by Alam et al. for canada_wildfires_2016 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the canada_wildfires_2016 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 76,484 tweets across 19 events, 10 humanitarian categories, collected by Alam et al. for 19 natural disaster events (2016-2019). Each record contains tweet text, humanitarian category label, event name, train/dev/test split. Largest publicly available human-annotated crisis dataset with 76,484 tweets across 19 events. Suitable for crisis informatics, humanitarian response, text classification, social media analysis.
A Twitter dataset of 3,933 tweets from cyclone_idai_2019, collected by Alam et al. for cyclone_idai_2019 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the cyclone_idai_2019 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 1,563 tweets from ecuador_earthquake_2016, collected by Alam et al. for ecuador_earthquake_2016 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the ecuador_earthquake_2016 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 1,515 tweets from greece_wildfires_2018, collected by Alam et al. for greece_wildfires_2018 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the greece_wildfires_2018 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 7,613 tweets from hurricane_dorian_2019, collected by Alam et al. for hurricane_dorian_2019 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the hurricane_dorian_2019 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 6,264 tweets from hurricane_florence_2018, collected by Alam et al. for hurricane_florence_2018 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the hurricane_florence_2018 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 9,112 tweets from hurricane_harvey_2017, collected by Alam et al. for hurricane_harvey_2017 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the hurricane_harvey_2017 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 9,399 tweets from hurricane_irma_2017, collected by Alam et al. for hurricane_irma_2017 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the hurricane_irma_2017 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 7,278 tweets from hurricane_maria_2017, collected by Alam et al. for hurricane_maria_2017 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the hurricane_maria_2017 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 1,654 tweets from hurricane_matthew_2016, collected by Alam et al. for hurricane_matthew_2016 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the hurricane_matthew_2016 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 1,201 tweets from italy_earthquake_aug_2016, collected by Alam et al. for italy_earthquake_aug_2016 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the italy_earthquake_aug_2016 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 2,195 tweets from kaikoura_earthquake_2016, collected by Alam et al. for kaikoura_earthquake_2016 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the kaikoura_earthquake_2016 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 7,984 tweets from kerala_floods_2018, collected by Alam et al. for kerala_floods_2018 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the kerala_floods_2018 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 742 tweets from maryland_floods_2018, collected by Alam et al. for maryland_floods_2018 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the maryland_floods_2018 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 1,880 tweets from midwestern_us_floods_2019, collected by Alam et al. for midwestern_us_floods_2019 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the midwestern_us_floods_2019 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 1,958 tweets from pakistan_earthquake_2019, collected by Alam et al. for pakistan_earthquake_2019 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the pakistan_earthquake_2019 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 2,015 tweets from puebla_mexico_earthquake_2017, collected by Alam et al. for puebla_mexico_earthquake_2017 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the puebla_mexico_earthquake_2017 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 560 tweets from srilanka_floods_2017, collected by Alam et al. for srilanka_floods_2017 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the srilanka_floods_2017 event. Suitable for crisis informatics, humanitarian response, text classification.
A Hyves (Dutch social network) dataset of 1,402,673 users and 2,777,419 friendship edges (avg degree 2.0), collected by Mahsa Mojtahedi via Hyves crawl (December 2010). Each record contains user-user friendship edges and user IDs. The dataset is notable for its very sparse friendship network from Hyves, the most popular social networking site in the Netherlands, competing with Facebook and MySpace. Intended for research into social network analysis, community detection, sparse network studies, and regional social media platform structure research.
A Rumble (alt-right video platform) dataset of 6,735 Rumble videos from 245 channels (2020-2023), collected by iDRAMA Lab via Rumble API (2024). Each record contains video ID, title, channel name, view/upvote/dislike/comment counts, follower count, video duration, description, named entities, tags, URL. 6,735 Rumble videos with full engagement metrics and NER annotations — one of few open datasets covering Rumble, a major alternative video platform popular with right-wing creators post-YouTube deplatforming. Suitable for alternative video platform research, deplatforming effects, political video discourse, engagement analysis, NER on video metadata.
A Rumble (alt-right video platform) — speech transcriptions dataset of 6,735 lite speech transcriptions from Rumble podcasts (2020-2023), collected by iDRAMA Lab via Whisper ASR (2024). Each record contains video ID, lite transcription segments, named entities (person/org/GPE). 6,735 Rumble podcast transcriptions enabling text-based analysis of spoken political content — rare speech-to-text dataset from an alternative video platform. Suitable for spoken political discourse analysis, NER on speech, alternative platform audio content research, misinformation in video content.
A Scored.co (alternative Reddit platform) dataset of 56,815,584 total posts and comments (6,293,980 submissions + 50,521,604 comments) from 964 communities, 2020-2023, collected by iDRAMA Lab via Scored.co API (2024). Each record contains post/comment text, author, community, score up/down, NSFW/image/video/deleted/twitter-crosspost flags, post flair, date, UUID. iDRAMA-Scored covers 6,293,980 submissions from Scored.co including banned communities like TheDonald and GreatAwakening that migrated from Reddit after deplatforming — 964 distinct communities, 131,691 unique authors. Suitable for deplatforming research, community migration, hate speech detection, alternative platform analysis, far-right discourse, content moderation effects.
A Instagram (beauty influencers) dataset of 436,843 posts from beauty influencers, collected by Seungbae Kim and Jinyoung Han (2020). Each record contains post caption text, like count, comment count, video/ad flags, tagged user count, location presence, image dimensions, timestamp, and influencer follower count. The dataset is notable for its subset of 9.7M-post Instagram influencer dataset covering the beauty category, with rich per-post engagement signals and influencer-level metadata. Intended for research into influencer marketing analysis, engagement prediction, social media content analysis, and sponsorship detection. This package holds the post metadata (one JSON .info file per post) and influencer lists; the post images, which the authors distribute separately on request, are not included.
A Instagram (family influencers) dataset of 1,170,485 posts from family influencers, collected by Seungbae Kim and Jinyoung Han (2020). Each record contains post caption text, like count, comment count, video/ad flags, tagged user count, location presence, image dimensions, timestamp, and influencer follower count. The dataset is notable for its subset of 9.7M-post Instagram influencer dataset covering the family category, with rich per-post engagement signals and influencer-level metadata. Intended for research into influencer marketing analysis, engagement prediction, social media content analysis, and sponsorship detection. This package holds the post metadata (one JSON .info file per post) and influencer lists; the post images, which the authors distribute separately on request, are not included.
A Instagram (fashion influencers) dataset of 3,411,944 posts from fashion influencers, collected by Seungbae Kim and Jinyoung Han (2020). Each record contains post caption text, like count, comment count, video/ad flags, tagged user count, location presence, image dimensions, timestamp, and influencer follower count. The dataset is notable for its subset of 9.7M-post Instagram influencer dataset covering the fashion category, with rich per-post engagement signals and influencer-level metadata. Intended for research into influencer marketing analysis, engagement prediction, social media content analysis, and sponsorship detection. This package holds the post metadata (one JSON .info file per post) and influencer lists; the post images, which the authors distribute separately on request, are not included.
A Instagram (fitness influencers) dataset of 319,414 posts from fitness influencers, collected by Seungbae Kim and Jinyoung Han (2020). Each record contains post caption text, like count, comment count, video/ad flags, tagged user count, location presence, image dimensions, timestamp, and influencer follower count. The dataset is notable for its subset of 9.7M-post Instagram influencer dataset covering the fitness category, with rich per-post engagement signals and influencer-level metadata. Intended for research into influencer marketing analysis, engagement prediction, social media content analysis, and sponsorship detection. This package holds the post metadata (one JSON .info file per post) and influencer lists; the post images, which the authors distribute separately on request, are not included.
A Instagram (food influencers) dataset of 1,039,706 posts from food influencers, collected by Seungbae Kim and Jinyoung Han (2020). Each record contains post caption text, like count, comment count, video/ad flags, tagged user count, location presence, image dimensions, timestamp, and influencer follower count. The dataset is notable for its subset of 9.7M-post Instagram influencer dataset covering the food category, with rich per-post engagement signals and influencer-level metadata. Intended for research into influencer marketing analysis, engagement prediction, social media content analysis, and sponsorship detection. This package holds the post metadata (one JSON .info file per post) and influencer lists; the post images, which the authors distribute separately on request, are not included.
A Instagram (interior influencers) dataset of 348,559 posts from interior influencers, collected by Seungbae Kim and Jinyoung Han (2020). Each record contains post caption text, like count, comment count, video/ad flags, tagged user count, location presence, image dimensions, timestamp, and influencer follower count. The dataset is notable for its subset of 9.7M-post Instagram influencer dataset covering the interior category, with rich per-post engagement signals and influencer-level metadata. Intended for research into influencer marketing analysis, engagement prediction, social media content analysis, and sponsorship detection. This package holds the post metadata (one JSON .info file per post) and influencer lists; the post images, which the authors distribute separately on request, are not included.
Deezer
GitHub
Gnutella
Google
The internet
Academia.edu
Twitter (X)
Reddit
YouTube
Hyves
Rumble
Scored
Instagram