Early activity diversity: Assessing newcomer retention from first-session activity

Raghav Pavan Karumur, Tien T. Nguyen, Joseph A. Konstan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

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 languageEnglish (US)
Title of host publicationProceedings of the 19th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2016
PublisherAssociation for Computing Machinery
Pages595-608
Number of pages14
ISBN (Electronic)9781450335928
DOIs
StatePublished - Feb 27 2016
Event19th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2016 - San Francisco, United States
Duration: Feb 27 2016Mar 2 2016

Publication series

NameProceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW
Volume27

Other

Other19th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2016
CountryUnited States
CitySan Francisco
Period2/27/163/2/16

Bibliographical note

Funding 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.

Keywords

  • Activity
  • Activity diversity
  • Dealing with newcomers
  • Early user experience
  • First session
  • Longevity
  • Newcomer engagement
  • Newcomer retention
  • Online communities

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