Research use only (no standard licence)

202 datasets tagged as the license “Research use only (no standard licence)”.

202 datasets.

Twitter 2010 Follower Network Analyzed

A Twitter (2010 snapshot) dataset of 41,652,230 users and 1,468,365,182 directed follower edges, collected by Kwak, Lee, Park & Moon via Twitter API (2010). Each record contains source user ID, follower user ID (edge from i to j means j follows i). Complete snapshot of the Twitter follower graph from 2010 — one of the largest social network datasets ever released publicly, capturing the full follower structure of 41.6M Twitter users with 1.47 billion directed edges.. Suitable for large-scale social network analysis, community detection, influence propagation, graph algorithm benchmarking, Twitter network evolution studies.

41.7M records41.7M nodes1.5B edges2010

rtGender — All Platforms (Cumulative) Analyzed

A Multiple Platforms dataset of 2,469,836 posts, 26,496,468 responses across 5 platforms, collected by Peixian and Zhang. Each record contains platform, posts, responses, op_gender, responder_gender, sentiment, relevance. Cumulative rtGender dataset combining all platforms for cross-platform gender analysis. Suitable for cross-platform gender analysis, sentiment comparison, response prediction.

29M records21.8M nodes23.9M edges2018

Foursquare Global Check-ins with Social Network (WWW 2019) Analyzed

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.

22.8M records114.3K nodes607.3K edges2019

rtGender — Facebook Congress Analyzed

A Facebook Congress dataset of 548,341 posts, 13,866,507 responses, collected by Peixian and Zhang. Each record contains posts, responses, op_gender, responder_gender, sentiment, relevance. rtGender dataset for Facebook Congress — studies gendered responses in online discourse. Suitable for gender studies, sentiment analysis, response prediction.

14.4M records9.5M nodes10.3M edges2018

LiveJournal Emotions Dataset (Jin & Zafarani 2017) Analyzed

A LiveJournal (blogging social network) dataset of 12,404,868 emotion-labeled posts from 115,444 users with 106,577 nodes and 961,392 friendship/follower edges, collected by Jin & Zafarani via LiveJournal API, distributed by Data Lab SU. Each record contains user ID, emotion label (-1=negative/0=neutral/1=positive), timestamp, friendship edges, follower edges, community membership. 12,404,868 LiveJournal posts labeled with trichotomous emotion scores across 115,444 users — uniquely combines social network structure (friendship + follower graphs) with per-post emotion labels and community membership for studying emotion propagation in networks. Suitable for emotion propagation in social networks, community emotion analysis, sentiment diffusion, social influence on emotion, network-based mood modeling.

12.4M records106.6K nodes961.4K edges2017

Twitter Social Network (Syracuse Data Lab) Analyzed

A Twitter dataset of 11,316,811 users and 85,331,843 directed follower/followee edges, collected by Zafarani and Liu at Syracuse University Data Lab. Each record contains directed edges from follower to followee; bare integer node IDs (anonymized users). one of the largest publicly available Twitter follower networks, with 85M directed edges enabling large-scale social network analysis at the full platform scale. Suitable for large-scale network analysis, influence propagation, community detection, centrality computation, and information diffusion modeling.

11.3M records11.3M nodes85.3M edges2026

rtGender — Facebook Wiki Analyzed

A Facebook Wiki dataset of 149,448 posts, 10,667,500 responses, collected by Peixian and Zhang. Each record contains posts, responses, op_gender, responder_gender, sentiment, relevance. rtGender dataset for Facebook Wiki — studies gendered responses in online discourse. Suitable for gender studies, sentiment analysis, response prediction.

10.8M records7.8M nodes8.3M edges2018

Amazon Movie Reviews Analyzed

A Amazon.com movie product pages dataset of 7,911,696 movie reviews spanning 1997 to 2012, collected by McAuley & Leskovec via Amazon product review pages (2013). Each record contains product ID, reviewer user ID, reviewer profile name, helpfulness votes (numerator/denominator), star rating (1-5), Unix timestamp, review summary, and full review text. One of the largest Amazon review datasets publicly available — 8 million movie reviews with full text, helpfulness votes, and star ratings spanning 15 years of Amazon movie reviews.. Suitable for sentiment analysis, review helpfulness prediction, recommendation systems, user expertise modeling, longitudinal review behavior analysis.

7.9M records2013

Friendster Social Network Analyzed

A Friendster (social network) dataset of 5,689,498 users and 14,067,887 friendship edges, collected by Booher via Friendster crawl (Nov 2010). Each record contains user-user friendship edges. classic social network dataset with 14M edges, representing one of the early major social networking platforms. Suitable for social network analysis, community detection, and friendship prediction.

5.7M records5.7M nodes14.1M edges2026

YouTube Snapshot 0222 Analyzed

A YouTube dataset of 743,569 videos, 14,338,803 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0222 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

3.8M records3.8M nodes14.3M edges2008

Instagram Influencer Dataset — Fashion Analyzed

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.

3.4M records2020

rtGender — Reddit Analyzed

A Reddit dataset of 1,453,512 posts, 1,453,512 responses, collected by Peixian and Zhang. Each record contains posts, responses, op_gender, responder_gender, sentiment, relevance. rtGender dataset for Reddit — studies gendered responses in online discourse. Suitable for gender studies, sentiment analysis, response prediction.

2.9M records3.5M nodes4M edges2018

Flixster Friendship Network (December 2010) Analyzed

A Flixster (social movie network) dataset of 2,523,386 users and 7,918,801 friendship edges, collected by Javier Parra via Flixster crawl (December 2010). Each record contains user-user friendship edges and user IDs. The dataset is notable for its friendship network from Flixster, a social movie site where users shared ratings, discovered films, and found others with similar tastes. Intended for research into social network analysis, community detection, movie recommendation systems, and taste-based social network studies.

2.5M records2.5M nodes7.9M edges2010

YouTube User Network (2008) Analyzed

A YouTube dataset of 2,139,109 users with 38,047,355 uploads and 40,088,341 friend relationships, collected by Cheng et al. via YouTube API (2007-2008). Each record contains user ID, number of uploaded videos, number of friends/subscriptions. YouTube user network from 2008 capturing user activity and friendship patterns during the platform's early growth period. Suitable for social network analysis, user behavior analysis, influencer identification, community detection.

2.1M records2.1M nodes2008

YouTube Snapshot 080327 Analyzed

A YouTube dataset of 309,314 videos, 4,444,600 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080327 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

1.8M records1.8M nodes4.4M edges2008

Instagram Influencer Dataset — Other Analyzed

A Instagram (other influencers) dataset of 1,625,526 posts from other 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 other 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.

1.6M records2020

YouTube Snapshot 0410 Analyzed

A YouTube dataset of 202,320 videos, 3,916,266 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0410 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

1.6M records1.6M nodes3.9M edges2008

Hyves Friendship Network (December 2010) Analyzed

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.

1.4M records1.4M nodes2.8M edges2010

YouTube Snapshot 080329 Analyzed

A YouTube dataset of 186,484 videos, 2,598,034 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080329 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

1.2M records1.2M nodes2.6M edges2008

Instagram Influencer Dataset — Travel Analyzed

A Instagram (travel influencers) dataset of 1,203,723 posts from travel 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 travel 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.

1.2M records2020

Instagram Influencer Dataset — Family Analyzed

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.

1.2M records2020

YouTube Snapshot 0301 Analyzed

A YouTube dataset of 154,817 videos, 2,969,826 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0301 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

1.2M records1.2M nodes3M edges2008

BookCrossing Interactions (implicit) Analyzed

The BookCrossing user–book network in its implicit form, as distributed by KONECT (bookcrossing_full-rating): 1,149,739 interactions between 105,278 members of the BookCrossing community and 340,523 books, collected by Cai-Nicolas Ziegler in August and September 2004. An edge records that a user interacted with a book; this version carries no rating values. Useful for collaborative filtering, implicit-feedback recommendation and the structure of user–item networks.

1.1M records445.8K nodes1.1M edges2005

YouTube (v2) Friendship Network Analyzed

A YouTube (friendship network) dataset of 1,138,499 users and 2,990,443 friendship edges, collected by Tang & Liu via YouTube crawl (2009). Each record contains user-user friendship edges, group memberships (47 groups), and user IDs. The dataset is notable for its classic social network dataset with explicit group memberships, used as a benchmark for latent social dimensions and collective behavior learning. Intended for research into social network analysis, community detection, group membership prediction, and relational learning in social media.

1.1M records1.1M nodes3M edges2009

YouTube Social Network Analyzed

A YouTube (friendship network) dataset of 1,134,890 nodes and 2,987,624 edges, collected by Mislove et al. via YouTube crawl (2007). Each record contains user-user friendship edges and user-defined group communities. The dataset is notable for its large-scale YouTube friendship network with ground-truth communities. Intended for research into community detection, social network analysis, and group membership prediction.

1.1M records1.1M nodes3M edges2007

YouTube User Network (2007) Analyzed

A YouTube dataset of 1,062,308 users with 11,757,702 uploads and 773,531,437 friend relationships, collected by Cheng et al. via YouTube API (2007-2008). Each record contains user ID, number of uploaded videos, number of friends/subscriptions, subscribers. YouTube user network from 2007 capturing user activity and friendship patterns during the platform's early growth period. Suitable for social network analysis, user behavior analysis, influencer identification, community detection.

1.1M records1.1M nodes2008

YouTube Snapshot 0420 Analyzed

A YouTube dataset of 111,860 videos, 2,179,497 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0420 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

1.1M records1.1M nodes2.2M edges2008

YouTube Snapshot 080404 Analyzed

A YouTube dataset of 155,060 videos, 2,171,719 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080404 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

1.1M records1.1M nodes2.2M edges2008

Instagram Influencer Dataset — Food Analyzed

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.

1M records2020

YouTube Snapshot 080331 Analyzed

A YouTube dataset of 149,933 videos, 2,057,770 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080331 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

999K records999K nodes2.1M edges2008

YouTube Snapshot 0313 Analyzed

A YouTube dataset of 117,752 videos, 2,254,098 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0313 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

983.1K records983.1K nodes2.3M edges2008

YouTube Snapshot 080402 Analyzed

A YouTube dataset of 154,228 videos, 2,025,178 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080402 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

975.5K records975.5K nodes2M edges2008

Fakeddit: Multimodal Fake News Detection Analyzed

A Fakeddit (multimodal fake news benchmark) dataset of 965,647 Reddit submissions with text, images and metadata, collected by Nakamura et al. via the Reddit API (2020). Each record holds the post title, text, image URL, comment count, score, timestamp and 2-, 3- and 6-way veracity labels (6-way: true, satire/parody, misleading content, imposter content, false connection, manipulated content). Suitable for fake news detection, multimodal learning and misinformation classification.

965.6K records2019

YouTube Snapshot 0329 Analyzed

A YouTube dataset of 103,162 videos, 1,993,886 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0329 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

919.1K records919.1K nodes2M edges2008

YouTube Snapshot 080422 Analyzed

A YouTube dataset of 133,611 videos, 1,735,389 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080422 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

893K records893K nodes1.7M edges2008

YouTube Snapshot 0418 Analyzed

A YouTube dataset of 91,638 videos, 1,784,291 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0418 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

889.1K records889.1K nodes1.8M edges2008

YouTube Snapshot 0403 Analyzed

A YouTube dataset of 101,346 videos, 1,938,311 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0403 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

883.4K records883.4K nodes1.9M edges2008

YouTube Snapshot 080408 Analyzed

A YouTube dataset of 133,073 videos, 1,757,884 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080408 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

877K records877K nodes1.8M edges2008

YouTube Snapshot 0422 Analyzed

A YouTube dataset of 88,823 videos, 1,733,223 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0422 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

867.9K records867.9K nodes1.7M edges2008

YouTube Snapshot 0430 Analyzed

A YouTube dataset of 84,512 videos, 1,646,352 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0430 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

864.1K records864.1K nodes1.6M edges2008

MySpace Aminer Social Graph (Follower Network) Analyzed

A MySpace dataset of 854,498 users, 6,489,736 directed follower edges, collected by Zhang and Tang via AMiner. Each record contains directed follower edges (source -> target means source follows target). Large-scale MySpace follower graph from AMiner, capturing social connections among 854K users. Suitable for social network analysis, community detection, influence propagation, graph embedding.

854.5K records854.5K nodes6.5M edges2013

YouTube Snapshot 080406 Analyzed

A YouTube dataset of 128,359 videos, 1,683,286 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080406 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

843.5K records843.5K nodes1.7M edges2008

YouTube Snapshot 080412 Analyzed

A YouTube dataset of 123,667 videos, 1,722,879 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080412 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

842.8K records842.8K nodes1.7M edges2008

YouTube Snapshot 0424 Analyzed

A YouTube dataset of 76,805 videos, 1,495,423 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0424 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

790.5K records790.5K nodes1.5M edges2008

YouTube Snapshot 080418 Analyzed

A YouTube dataset of 114,041 videos, 1,554,267 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080418 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

777.5K records777.5K nodes1.6M edges2008

YouTube Snapshot 0413 Analyzed

A YouTube dataset of 83,135 videos, 1,607,219 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0413 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

772.6K records772.6K nodes1.6M edges2008

Digg Friendship Network (December 2010) Analyzed

A Digg (social news) dataset of 771,231 users and 5,911,205 friendship edges, collected by Mithila Nagendra via Digg crawl (December 2010). Each record contains user-user friendship edges and user IDs. The dataset is notable for its friendship network from the pre-v4 Digg social news platform, where users voted stories up (digging) or down (burying). Intended for research into social network analysis, community detection, information diffusion, and social news platform structure studies.

771.2K records771.2K nodes5.9M edges2010

YouTube Snapshot 0428 Analyzed

A YouTube dataset of 71,715 videos, 1,397,970 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0428 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

743K records743K nodes1.4M edges2008

YouTube Snapshot 080424 Analyzed

A YouTube dataset of 110,122 videos, 1,392,317 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080424 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

735.1K records735.1K nodes1.4M edges2008

YouTube Snapshot 080430 Analyzed

A YouTube dataset of 102,847 videos, 1,325,498 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080430 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

701.9K records701.9K nodes1.3M edges2008