Design for network communities
Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
Information Systems Research
Group formation in large social networks: membership, growth, and evolution
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
The life and death of online gaming communities: a look at guilds in world of warcraft
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Measurement and analysis of online social networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Statistical properties of community structure in large social and information networks
Proceedings of the 17th international conference on World Wide Web
Co-evolution of social and affiliation networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Inferring networks of diffusion and influence
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Defining and evaluating network communities based on ground-truth
Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics
Composing activity groups in social networks
Proceedings of the 21st ACM international conference on Information and knowledge management
Multi-scale dynamics in a massive online social network
Proceedings of the 2012 ACM conference on Internet measurement conference
Distinguishing topical and social groups based on common identity and bond theory
Proceedings of the sixth ACM international conference on Web search and data mining
Predicting group evolution in the social network
SocInfo'12 Proceedings of the 4th international conference on Social Informatics
Identification of Group Changes in Blogosphere
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
No country for old members: user lifecycle and linguistic change in online communities
Proceedings of the 22nd international conference on World Wide Web
Predicting group stability in online social networks
Proceedings of the 22nd international conference on World Wide Web
Social resilience in online communities: the autopsy of friendster
Proceedings of the first ACM conference on Online social networks
The role of founders in building online groups
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
Modeling and predicting the growth and death of membership-based websites
Proceedings of the 23rd international conference on World wide web
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We pose a fundamental question in understanding how to identify and design successful communities: What factors predict whether a community will grow and survive in the long term? Social scientists have addressed this question extensively by analyzing offline groups which endeavor to attract new members, such as social movements, finding that new individuals are influenced strongly by their ties to members of the group. As a result, prior work on the growth of communities has treated growth primarily as a diffusion processes, leading to findings about group evolution which can be difficult to explain. The proliferation of online social networks and communities, however, has created new opportunities to study, at a large scale and with very fine resolution, the mechanisms which lead to the formation, growth, and demise of online groups. In this paper, we analyze data from several thousand online social networks built on the Ning platform with the goal of understanding the factors contributing to the growth and longevity of groups within these networks. Specifically, we investigate the role that two types of growth (growth through diffusion and growth by other means) play during a group's formative stages from the perspectives of both the individual member and the group. Applying these insights to a population of groups of different ages and sizes, we build a model to classify groups which will grow rapidly over the short-term and long-term. Our model achieves over 79% accuracy in predicting group growth over the following two months and over 78% accuracy in predictions over the following two years. We utilize a similar approach to predict which groups will die within a year. The results of our combined analysis provide insight into how both early non-diffusion growth and a complex set of network constraints appear to contribute to the initial and continued growth and success of groups within social networks. Finally we discuss implications of this work for the design, maintenance, and analysis of online communities.