Maximizing the spread of influence through a social network
Proceedings of the ninth 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
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
Efficient influence maximization in social networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Social influence analysis in large-scale networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Social influence and the diffusion of user-created content
Proceedings of the 10th ACM conference on Electronic commerce
Learning influence probabilities in social networks
Proceedings of the third ACM international conference on Web search and data mining
Randomization tests for distinguishing social influence and homophily effects
Proceedings of the 19th international conference on World wide web
Inferring networks of diffusion and influence
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
Mining topic-level influence in heterogeneous networks
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
User-level sentiment analysis incorporating social networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
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Social influence is the behavioral change of a person because of the perceived relationship with other people, organizations and society in general. Social influence has been a widely accepted phenomenon in social networks for decades. Many applications have been built based around the implicit notation of social influence between people, such as marketing, advertisement and recommendations. With the exponential growth of online social network services such as Facebook and Twitter, social influence can for the first time be measured over a large population. In this tutorial, we survey the research on social influence analysis with a focus on the computational aspects. First, we introduce how to verify the existence of social influence in various social networks. Second, we present computational models for quantifying social influence. Third, we describe how social influence can help real applications. In particular, we will focus on opinion leader finding and influence maximization for viral marketing. Finally, we apply the selected algorithms of social influence analysis on different social network data, such as twitter, arnetminer data, weibo, and slashdot forum.