CHS: Small: A Genealogical Framework to Understand the Emergence of Online Groups

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The project will study the emergence of online groups by examining their overlooked but important connections to existing groups. New online groups do not appear spontaneously, but are created by users who participated in existing online groups. A new group's early members carry their own activity history, which reveals their past group memberships as well as the relations between existing groups and this new group. The ability to trace the behavior of users before they start new groups presents a unique opportunity to understand how new groups emerge, how social norms arise in new groups, and what factors contribute to the success of new groups. This research will quantitatively model the genealogical relationships between online groups by tracing the sociotechnical lineage of "child" groups through their early members' previous participation in "parent" groups. Platform administrators or group moderators can use genealogical approaches for adopting existing norms in other groups, recommending new groups to users, and identifying opportunities to create new groups. A genealogical perspective can also explain the variability in group success as well as how norms spread throughout online groups. This work will enable transformative changes in online communities, either via redesign of their platforms or through implementation of new community policies.The project draws on theories about formation of online communities, organizational ecology, and kinship to explore how a group's position within a genealogical graph influences the group's identity, norms, and success. This research will analyze log data about user behavior over time from Reddit and Wikipedia. Aggregating the socio-technical lineages of multiple groups together generates a genealogical graph documenting how new groups emerge from the old. These genealogies will be evaluated across platforms, users, and time. The project will advance human-centered data science methods by employing qualitative methods, such as interviews and focus groups, to validate the proposed genealogical graphs, which will inform quantitative methods for building genealogy graphs from large-scale log data sets and analyzing their structure and dynamics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.