Maybe you’ve joined a group recently could be a Taekwondo group, a wine tasting club, a fantasy football league, or whatever. Do you know that how people felt “connected” to a group before they joined can predict their future behavior in the group? Social psychologists have identified two conceptually distinct ways a member can connect with a group — identity-based attachment (e.g., “I feel connected to the Taekwondo group because I started to learn Taekwondo when I was a kid!”) and bonds-based attachment (e.g., “I feel connected to the wine tasting club because my best friend Daniel is a club member!”) — and worked to understand their causes and consequences. What we have done is study how connections between a person and an online group can predict that person’s future behavior.

Specifically, we studied WikiProjects, self-organizing groups of Wikipedia editors dedicated to improving articles on some topic, e.g., video games, military history, or the state of Minnesota. We operationalized identity-based attachment by matching editors’ interest and the topic of WikiProjects, and bonds-based attachment by measuring how well new group members were connected to existing members. We investigated how the two types of attachment predicted editors’ productivity (the number of edits they made in the project) and withdrawal (whether the editor left the project within six months).

We found that both types of attachment increased editors’ productivity and decreased their likelihood of withdrawing the group, but in slightly different ways. Editors with stronger identity-based attachment (one standard deviation above the mean) edited 17% more after joining a project, while editors with stronger bonds-based attachment (again, one standard deviation higher) had a 9% lower likelihood of leaving the project. Both numbers are statistically significant.

What can we learn from this study? Our results suggest targeted recruitment strategies for groups within a larger online community (Wikiprojects, subreddits, etc.). Specifically, a tool could identify people with existing ‘attachments’ to a group that indicate they are likely to be prolific editors and/or stay in the group for the long haul, and then craft personalized invitations to invite them to participate in the group. For very large online communities, e.g., with over 100K users, such a tool could automatically execute new member identification and invitation tasks, and reduce the workload of existing group members.

Our study was published in CSCW 2017, and is titled: Predicting Member Productivity and Withdrawal from Pre-Joining Attachments in Online Production Groups. For more detail, check out our paper.


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Bowen is a fourth year PhD student co-advised by Haiyi Zhu and Loren Terveen. He is interested in understanding the mechanisms behind online user behaviors and interactions, and building systems and tools to facilitate user collaboration.

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