Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
The link-prediction problem for social networks
Journal of the American Society for Information Science and Technology
Preferential behavior in online groups
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Local Probabilistic Models for Link Prediction
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Why We Twitter: An Analysis of a Microblogging Community
Advances in Web Mining and Web Usage Analysis
Social influence analysis in large-scale networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Relationship identification for social network discovery
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
TwitterRank: finding topic-sensitive influential twitterers
Proceedings of the third ACM international conference on Web search and data mining
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
Predicting positive and negative links in online social networks
Proceedings of the 19th international conference on World wide web
Earthquake shakes Twitter users: real-time event detection by social sensors
Proceedings of the 19th international conference on World wide web
Networks, Crowds, and Markets: Reasoning About a Highly Connected World
Networks, Crowds, and Markets: Reasoning About a Highly Connected World
TwitterMonitor: trend detection over the twitter stream
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Mining advisor-advisee relationships from research publication networks
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
New perspectives and methods in link prediction
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Social action tracking via noise tolerant time-varying factor graphs
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Understanding retweeting behaviors in social networks
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Supervised random walks: predicting and recommending links in social networks
Proceedings of the fourth ACM international conference on Web search and data mining
Who says what to whom on twitter
Proceedings of the 20th international conference on World wide web
User-level sentiment analysis incorporating social networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Detecting the structure of social networks using (α, β)-communities
WAW'11 Proceedings of the 8th international conference on Algorithms and models for the web graph
Learning to infer social ties in large networks
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Who will follow you back?: reciprocal relationship prediction
Proceedings of the 20th ACM international conference on Information and knowledge management
Loopy belief propagation for approximate inference: an empirical study
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
A generalized mean field algorithm for variational inference in exponential families
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Inferring social ties across heterogenous networks
Proceedings of the fifth ACM international conference on Web search and data mining
Cross-domain collaboration recommendation
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Actively learning to infer social ties
Data Mining and Knowledge Discovery
Recommending program committee candidates for academic conferences
Proceedings of the 2013 workshop on Computational scientometrics: theory & applications
| Hi-index | 0.00 |
We study how links are formed in social networks. In particular, we focus on investigating how a reciprocal (two-way) link, the basic relationship in social networks, is developed from a parasocial (one-way) relationship and how the relationships further develop into triadic closure, one of the fundamental processes of link formation. We first investigate how geographic distance and interactions between users influence the formation of link structure among users. Then we study how social theories including homophily, social balance, and social status are satisfied over networks with parasocial and reciprocal relationships. The study unveils several interesting phenomena. For example, “friend's friend is a friend” indeed exists in the reciprocal relationship network, but does not hold in the parasocial relationship network. We propose a learning framework to formulate the problems of predicting reciprocity and triadic closure into a graphical model. We demonstrate that it is possible to accurately infer 90% of reciprocal relationships in a Twitter network. The proposed model also achieves better performance (+20--30% in terms of F1-measure) than several alternative methods for predicting the triadic closure formation.