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» Mining Antagonistic Communities from Social Networks
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KDD
2012
ACM
220views Data Mining» more  KDD 2012»
11 years 10 months ago
ComSoc: adaptive transfer of user behaviors over composite social network
Accurate prediction of user behaviors is important for many social media applications, including social marketing, personalization and recommendation, etc. A major challenge lies ...
ErHeng Zhong, Wei Fan, Junwei Wang, Lei Xiao, Yong...
SDM
2009
SIAM
331views Data Mining» more  SDM 2009»
14 years 5 months ago
Privacy Preservation in Social Networks with Sensitive Edge Weights.
With the development of emerging social networks, such as Facebook and MySpace, security and privacy threats arising from social network analysis bring a risk of disclosure of con...
Jie Wang, Jinze Liu, Jun Zhang, Lian Liu
WSDM
2012
ACM
352views Data Mining» more  WSDM 2012»
12 years 3 months ago
Multi-relational matrix factorization using bayesian personalized ranking for social network data
A key element of the social networks on the internet such as Facebook and Flickr is that they encourage users to create connections between themselves, other users and objects. On...
Artus Krohn-Grimberghe, Lucas Drumond, Christoph F...
CIKM
2010
Springer
13 years 6 months ago
Understanding retweeting behaviors in social networks
Retweeting is an important action (behavior) on Twitter, indicating the behavior that users re-post microblogs of their friends. While much work has been conducted for mining text...
Zi Yang, Jingyi Guo, Keke Cai, Jie Tang, Juanzi Li...
KDD
2010
ACM
265views Data Mining» more  KDD 2010»
13 years 9 months ago
Scalable influence maximization for prevalent viral marketing in large-scale social networks
Influence maximization, defined by Kempe, Kleinberg, and Tardos (2003), is the problem of finding a small set of seed nodes in a social network that maximizes the spread of influe...
Wei Chen, Chi Wang, Yajun Wang