Social Computing Data Repository - Basic Information ========================================================================== Dataset Name: Flickr Abstract: Flickr is an image hosting and video hosting website, web services suite, and online community. Number of Nodes: 80,513 Number of Edges: 5,899,882 Number of Groups: 195 Missing Values: No Source: ========================================================================== Lei Tang*, Huan Liu* * School of Computing, Informatics and Decision Systems Engineering, Arizona State University. E-mail: email@example.com, firstname.lastname@example.org Data Set Information: ========================================================================== [I]. Brief description This is the data set crawled from Flickr ( http://www.Flickr.com ). Flickr is an image hosting and video hosting website, web services suite, and online community. This contains the friendship network crawled and group memberships. For easier understanding, all the contents are organized in CSV file format. [II]. Basic statistics Number of users : 80,513 Number of friendship pairs: 5,899,882 Number of groups: 195 [III]. The data format 4 files are included: 1. nodes.csv -- it's the file of all the users. This file works as a dictionary of all the users in this data set. It's useful for fast reference. It contains all the node ids used in the dataset 2. groups.csv -- it's the file of all the groups. It contains all the group ids used in the dataset 3. edges.csv -- this is the friendship network among the users. The user's friends are represented using edges. Since the network is symmetric, each edge is represented only once. Here is an example. 1,2 This means user with id "1" is friend with user id "2". 4. group-edges.csv -- the user-group membership. In each line, the first entry represents user, and the 2nd entry is the group index. If you need to know more details, please check the relevant papers and code: http://www.public.asu.edu/~ltang9/social_dimension.html Relevant Papers: ========================================================================== 1. Lei Tang and Huan Liu. Relational Learning via Latent Social Dimensions. In Proceedings of The 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD�09), Pages 817�826, 2009. 2. Lei Tang and Huan Liu. Scalable Learning of Collective Behavior based on Sparse Social Dimensions. In Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM�09), 2009.