On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Small worlds: the dynamics of networks between order and randomness
Small worlds: the dynamics of networks between order and randomness
The "DGX" distribution for mining massive, skewed data
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Statistical mechanics of complex networks
Statistical mechanics of complex networks
Graphs over time: densification laws, shrinking diameters and possible explanations
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
On nash equilibria for a network creation game
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Graph mining: Laws, generators, and algorithms
ACM Computing Surveys (CSUR)
The price of anarchy in network creation games
Proceedings of the twenty-sixth annual ACM symposium on Principles of distributed computing
Effective label acquisition for collective classification
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Weighted graphs and disconnected components: patterns and a generator
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
RTM: Laws and a Recursive Generator for Weighted Time-Evolving Graphs
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Trajectory Outlier Detection: A Partition-and-Detect Framework
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Large human communication networks: patterns and a utility-driven generator
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
RTG: A Recursive Realistic Graph Generator Using Random Typing
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Finding Cohesive Subgroups and Relevant Members in the Nokia Friend View Mobile Social Network
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
Signed networks in social media
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Realistic, mathematically tractable graph generation and evolution, using kronecker multiplication
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
ComSoc: adaptive transfer of user behaviors over composite social network
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
ciForager: Incrementally discovering regions of correlated change in evolving graphs
ACM Transactions on Knowledge Discovery from Data (TKDD)
Modeling the dynamics of composite social networks
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
User behavior learning and transfer in composite social networks
ACM Transactions on Knowledge Discovery from Data (TKDD) - Casin special issue
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On-line social networking sites often involve multiple relations simultaneously. While people can build an explicit social network by adding each other as friends, they can also form several implicit social networks through their daily interactions like commenting on people's posts, or tagging people's photos. So given a real social networking system which changes over time, what can we say about people's social behaviors ? Do their daily interactions follow any pattern ? The majority of earlier work mainly mimics the patterns and properties of a single type of network. Here, we model the formation and co-evolution of multi-modal networks emerging from different social relations such as "who-adds-whom-as-friend" and "who-comments-on-whose-post" simultaneously. The contributions are the following : (a) we propose a new approach called EigenNetwork Analysis for analyzing time-evolving networks, and use it to discover temporal patterns with people's social interactions; (b) we report inherent correlation between friendship and co-occurrence in on-line settings; (c) we design the first multimodal graph generator xSocial 1 that is capable of producing multiple weighted time-evolving networks, which match most of the observed patterns so far. Our study was performed on two real datasets (Nokia FriendView and Flickr) with 100,000 and 50,000,000 records respectively, each of which corresponds to a different social service, and spans up to two years of activity.