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ego_social — Ego networks in social media (2012)

Description

Ego networks of users of Facebook, Google+ and Twitter, collected by J. McAuley and J. Leskovec to study how users organize their friends into social circles. An ego network consists of the friends of a user (the ego) and the connections among them, where the ego is not included as a node. The Facebook data were collected from survey participants through a Facebook app, and include the users' manually labeled circles (friend lists). The Google+ data were crawled in 2012 from users who had manually shared their circles using the "share circle" feature, and the Twitter data from public sources (lists). Node features (profile information) are given as binary vectors; for Facebook, the feature values have been anonymized, so that only the kind of feature (e.g. birthday, education;school;id) can be identified.

There are several networks:

  • facebook_<ego>: the 10 Facebook ego networks (undirected), named by the identifier of the ego;
  • facebook_combined: the union of all Facebook ego networks (undirected, including the egos), with 4,039 users;
  • gplus_<ego>: the Google+ ego networks (directed), named by the identifier of the ego (the 131 ego networks of the source with at least one edge);
  • gplus_combined: the union of all Google+ ego networks (directed), with 107,614 users;
  • twitter_<ego>: the 973 Twitter ego networks (directed), named by the identifier of the ego;
  • twitter_combined: the union of all Twitter ego networks (directed), with 81,306 users.

Nodes are users. In Facebook, an undirected edge means that the two users are friends; in Google+ and Twitter, a directed edge $i \to j$ means that user $i$ follows user $j$. For Twitter, the features are the hashtags (e.g. #python) and user mentions (e.g. @nytimes) used by the users. The features of the egos themselves are not included.

The networks have the following properties:

  • (Node) name (ego networks): the identifier of the user.
  • (Node) feat (ego networks): the binary feature vector of the user.
  • (Node) circles (ego networks): the list of circles of the ego to which the user belongs, each identified by its index (starting from 0) in the list of circles of the ego in the source data.
  • (Graph) feat_names (ego networks): a dictionary mapping each position of the feature vector to the name of the feature (e.g. gender:1 or birthday;anonymized feature 0).
Tags
Social Online Unweighted Metadata
Added
2020-08-11
Citation
  • J. McAuley and J. Leskovec. "Learning to Discover Social Circles in Ego Networks." NIPS (2012). arxiv:1210.8182 arXiv:1210.8182
Upstream URL OK
https://snap.stanford.edu/data/egonets-Facebook.html
https://snap.stanford.edu/data/egonets-Gplus.html
https://snap.stanford.edu/data/egonets-Twitter.html
Networks
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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
twitter_248523038 — — — — — — — — — — 7 KiB N/A N/A N/A
twitter_248883350 — — — — — — — — — — 28 KiB N/A N/A N/A
twitter_248916246 — — — — — — — — — — 30 KiB N/A N/A N/A
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Ridiculograms*
* These are automatically generated force-directed visualizations, and can be quite meaningless for networks both big and small. They should not be taken seriously as sources of scientific insight. See here for a discussion.