Online communities suffer serious newcomer attrition. This paper explores whether and how early activity diversity - The degree to which a newcomer engages in a wide range of a site's activities in the first session - is associated with their longevity. We introduce a metric (DSCORE) to characterize early activity diversity in online sites and run our analyses on an online community 'MovieLens'. We find that DSCORE is significant both by itself and in conjunction with a measure of quantity of activity in predicting longevity. This finding is robust to different measures of longevity (aggregate number of sessions and attritions after sessions 1, 5, and 10). The immediate implication is an effective classifier for identifying users with higher (or lower) expected longevity from the first-session activity. We also find DSCORE is more useful than a traditional measure of measuring diversity such as the Gini-Simpson index. We conclude by discussing how early activity diversity may be more broadly effective in supporting design and management of online communities.
|Original language||English (US)|
|Title of host publication||Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2016|
|Publisher||Association for Computing Machinery|
|Number of pages||14|
|State||Published - Feb 27 2016|
|Event||19th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2016 - San Francisco, United States|
Duration: Feb 27 2016 → Mar 2 2016
|Name||Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW|
|Other||19th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2016|
|Period||2/27/16 → 3/2/16|
Bibliographical noteFunding Information:
Acknowledgments This work was supported by the National Science Foundation under grants IIS 0808692, 1017697, 1319382, and Fellowship support from the University of Minnesota Informatics Institute. We also acknowledge the thoughtful discussions and helpful feedback from several members of the Grouplens Research lab along with their assistance in development of the classification tree. We thank the consultants at the Statistical Consulting Center and the Biostatistics Consulting Unit at the University of Minnesota for reviewing our statistical analyses. We also thank the anonymous reviewers for their valuable comments.
© 2016 ACM.
- Activity diversity
- Dealing with newcomers
- Early user experience
- First session
- Newcomer engagement
- Newcomer retention
- Online communities