Did they login? Patterns of anonymous contributions in online communities

Corey Brian Jackson, Kevin Crowston, Carsten Osterlund

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Researchers studying user behaviors in online communities often conduct analyses of user interaction data recorded in system logs e.g., an edit in Wikipedia. Such analysis relies on collating interactions by a unique identifier such as a user ID. However, if users can contribute without being logged-in (i.e., anonymously) analysis of interaction data omit part of a user’s experience. Problematically, anonymous traces are unlikely to be randomly distributed, so their omission can change statistical conclusions, with implications for both research and practice. To understand the impacts on conclusions of leaving out anonymous traces, we conducted an analysis of system logs from two online citizen science projects. Attributing anonymous traces with user IDs, we found that (1) many users contribute anonymously, though with varied patterns; and (2) attributing anonymous traces diminishes empirical evidence used to support theory and change the results of system algorithms. These results suggest anonymous traces have implications for research on user behaviors and the practices associated with using such data to tailor user experiences in online communities.

Original languageEnglish (US)
Article number77
JournalProceedings of the ACM on Human-Computer Interaction
Volume2
Issue numberCSCW
DOIs
StatePublished - Nov 2018

Keywords

  • Anonymity
  • Citizen science
  • Online communities
  • User behavior
  • Zooniverse

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Social Sciences (miscellaneous)

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