Mining knowledge-sharing sites for viral marketing
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Information diffusion through blogspace
Proceedings of the 13th international conference on World Wide Web
The predictive power of online chatter
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
The political blogosphere and the 2004 U.S. election: divided they blog
Proceedings of the 3rd international workshop on Link discovery
The dynamics of viral marketing
ACM Transactions on the Web (TWEB)
A Method for Estimating the Precision of Placename Matching
IEEE Transactions on Knowledge and Data Engineering
Cost-effective outbreak detection in networks
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Identifying the influential bloggers in a community
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Yes, there is a correlation: - from social networks to personal behavior on the web
Proceedings of the 17th international conference on World Wide Web
Iclone: towards online social navigation
Proceedings of the nineteenth ACM conference on Hypertext and hypermedia
The convergence of social and technological networks
Communications of the ACM - Remembering Jim Gray
Influence and correlation in social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Feedback effects between similarity and social influence in online communities
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Microscopic evolution of social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient sampling of information in social networks
Proceedings of the 2008 ACM workshop on Search in social media
Enabling Social Navigation on the Web
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Camera brand congruence in the Flickr social graph
Proceedings of the Second ACM International Conference on Web Search and Data Mining
A measurement-driven analysis of information propagation in the flickr social network
Proceedings of the 18th international conference on World wide web
Meme-tracking and the dynamics of the news cycle
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Individual and social behavior in tagging systems
Proceedings of the 20th ACM conference on Hypertext and hypermedia
Social influence and the diffusion of user-created content
Proceedings of the 10th ACM conference on Electronic commerce
Randomization tests for distinguishing social influence and homophily effects
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
Modeling user posting behavior on social media
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
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The capacity to collect and analyze the actions of individuals in online social systems at minute-by-minute time granularity offers new perspectives on collective human behavior research. Macroscopic analysis of massive datasets raises interesting observations of patterns in online social processes. But working at a large scale has its own limitations, since it typically doesn't allow for interpretations on a microscopic level. We examine how different types of individual behavior affect the decisions of friends in a network. We begin with the problem of detecting social influence in a social system. Then we investigate the causality between individual behavior and social influence by observing the diffusion of an innovation among social peers. Are more active users more influential? Are more credible users more influential? Bridging this gap and finding points where the macroscopic and microscopic worlds converge contributes to better interpretations of the mechanisms of spreading of ideas and behaviors in networks and offer design opportunities for online social systems.