Google+ Social Networks with Node Attributes
If you use our dataset in your papers, please cite the following papers.
Neil Zhenqiang Gong, Wenchang Xu, Ling Huang, Prateek Mittal, Emil Stefanov, Vyas Sekar and Dawn Song. "Evolution of Social-Attribute Networks: Measurements, Modeling, and Implications using Google+". In ACM/USENIX Internet Measurement Conference (IMC), 2012.
Neil Zhenqiang Gong, Ameet Talwalkar, Lester Mackey, Ling Huang, Eui Chul Richard Shin, Emil Stefanov, Elaine(Runting) Shi and Dawn Song . "Jointly Predicting Links and Inferring Attributes using a Social-Attribute Network (SAN)". In ACM Workshop on Social Network Mining and Analysis (SNA-KDD), 2012.
This published dataset consisting of 4 Google+ snapshots is a subset of the dataset studied in our IMC'12 paper. Each snapshot includes both directed social structure and node attributes, which can be represented by the following Social-Attribute Network. Snapshots 3 and 4 were crawled after Google+ was opened to the public.
Table I. Dataset summary
Directed social structure
UserIDFrom UserIDTo TimeID
Each line corresponds to a directed link. UserIDs are anonimyzed to be integers starting from 0. TimeID is 0, 1, 2 or 3, indicating which snapshot this directed link appears in.
UserID AttriID TimeID
Each line corresponds to an undirected attribute link. AttriID are anonimyzed to be negative integers starting from -1. Again, TimeID is 0, 1, 2 or 3, indicating which snapshot this directed link appears in.
Each line corresponds to an attribute. AttriType could be employer, school, major or places_lived.
Dataset Release Policy
To download the dataset, please send emails to Neil Zhenqiang Gong (email@example.com) with "[G+ Request]" in the subject. We will tell you the links to download the dataset. In your email, please include the following information (if we
don't know each other).
The information is needed for verification
If your papers use our dataset, please cite our papers.
You're not allowed to further distribute the dataset without our permission.
- A short description about what you're going to do with our dataset. Some keywords (e.g., link prediction, attribute inference, evolution) are enough. We don't need to know details.
Sending us emails for our dataset implies that you are aware of and agree with the above policies.