2018/03/20 by Yaniv Dover, Jacob Goldenberg, Dover, Yaniv +3
Computer Science · Physics and Astronomy · Social Sciences · #Complex Network Analysis Techniques #FOS: Computer and information sciences #FOS: Physical sciences #Opinion Dynamics and Social Influence #Physics and Society (physics.soc-ph) #Social Media and Politics #Social and Information Networks (cs.SI) #Statistical Mechanics (cond-mat.stat-mech) #cond-mat.stat-mech #cs.SI #physics.soc-ph
paper · pdf · doi:10.48550/arxiv.1803.07387
arxiv created 2018/03/20 · openalex publication_date 2018/03/20 · arxiv updated 2018/03/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Online communities exist in many forms and sizes, and are a source of considerable influence for individuals and organizations. Yet, there is limited insight into why some online communities are sustainable, while others cease to exist. We find that communities that fail to maintain a typical hierarchical social structure which balances cohesiveness across size scales do not survive, and can be distinguished from communities that exhibit such balance and prevail in the long term. Moreover, in an analysis of 10,122 real-life online communities with a total of 134,747 members over a period of more than a decade, we find that mapping the community social circle structure in the first 30 days of its lifetime is sufficient to forecast the survival of the community up to ten years in the future. By varying calibration time frames, the aspects of the social structure that allows for predictive power emerge and fixate within the first couple of months in a community's lifetime.