social_dimensions — BlogCatalog, Flickr and YouTube friendships with groups (2009)
- Description
Friendship networks of three social media websites, with the group memberships of the users, collected by L. Tang and H. Liu (Arizona State University) to study collective behaviour and the prediction of user attributes ("social dimensions"), and distributed by the Social Computing Data Repository (originally at Arizona State University, now at Syracuse University). In all networks, nodes are users, and an undirected edge connects two users who are friends (contacts) on the website. The group memberships of the users (in groups of interest of the site, selected by the authors) are given as a node property, and serve as labels in classification tasks.
blogcatalog: bloggers of the blog directory BlogCatalog (10,312 users, 333,983 friendships, 39 groups).flickr: users of the photo sharing site Flickr (80,513 users, 5,899,882 friendships, 195 groups).youtube: users of the video sharing site YouTube (1,138,499 users, 2,990,443 friendships, 47 groups; only 31,703 users belong to some group).
The networks have the following properties:
groups: the identifiers of the groups the user belongs to (the names of the groups are not given in the source data).
- Tags
- Social Online Unweighted Metadata
- Citation
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- L. Tang, H. Liu, "Relational learning via latent social dimensions." Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 817-826 (2009) 10.1145/1557019.1557109 Sci-Hub
- L. Tang, H. Liu, "Scalable learning of collective behavior based on sparse social dimensions." Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM), 1107-1116 (2009) 10.1145/1645953.1646094 Sci-Hub
- Upstream URL OK
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https://datasets.syr.edu/
https://web.archive.org/web/2014/http://www.public.asu.edu/~ltang9/social_dimension.html - Networks
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Tip: click on a column header to sort the list, or hover over it for a description.
Column legend
- $\left<k\right>$
- Mean degree
- $\sigma_k$
- Standard deviation of the degrees
- $\lambda_h$
- Largest eigenvalue of the Hashimoto (non-backtracking) matrix
- $\tau$
- Random walk mixing time
- $r$
- Degree assortativity
- $c$
- Global clustering coefficient
- $\oslash$
- (Pseudo-) diameter
- $S$
- Relative size of the largest component
- NPs
- Node properties
- EPs
- Edge properties
Name Nodes Edges $\left<k\right>$ $\sigma_k$ $\lambda_h$ $\tau$ $r$ $c$ $\oslash$ $S$ Kind Mode NPs EPs gt GraphML GML csv blogcatalog 10,312 333,983 64.78 177.70 321.14 1.77 -0.25 0.09 5 1.00 Undirected Unipartite groups 418 KiB 990 KiB 1017 KiB 932 KiB flickr 80,513 5,899,882 146.56 294.33 1086.25 16.48 0.07 0.19 6 1.00 Undirected Unipartite groups 8.3 MiB 17.0 MiB 16.6 MiB 17.2 MiB youtube 1,138,499 2,990,443 5.25 50.67 185.14 492.50 -0.04 0.01 24 1.00 Undirected Unipartite groups 6.6 MiB 11.4 MiB 11.3 MiB 13.1 MiB