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Santos Tiago, Walk Simon, Kern Roman, Strohmaier Markus, Helic Denis

Activity Archetypes in Question-and-Answer (Q8A) Websites—A Study of 50 Stack Exchange Instances

ACM Transactions on Social Computing, 2019

Millions of users on the Internet discuss a variety of topics on Question-and-Answer (Q&A) instances. However, not all instances and topics receive the same amount of attention, as some thrive and achieve selfsustaining levels of activity, while others fail to attract users and either never grow beyond being a smallniche community or become inactive. Hence, it is imperative to not only better understand but also to distilldeciding factors and rules that define and govern sustainable Q&A instances. We aim to empower communitymanagers with quantitative methods for them to better understand, control, and foster their communities,and thus contribute to making the Web a more efficient place to exchange information. To that end, we extract, model, and cluster a user activity-based time series from 50 randomly selected Q&A instances from theStack Exchange network to characterize user behavior. We find four distinct types of user activity temporalpatterns, which vary primarily according to the users’ activity frequency. Finally, by breaking down totalactivity in our 50 Q&A instances by the previously identified user activity profiles, we classify those 50 Q&Ainstances into three different activity profiles. Our parsimonious categorization of Q&A instances aligns withthe stage of development and maturity of the underlying communities, and can potentially help operatorsof such instances: We not only quantitatively assess progress of Q&A instances, but we also derive practicalimplications for optimizing Q&A community building efforts, as we, e.g., recommend which user types tofocus on at different developmental stages of a Q&A community
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