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

摘要

Millions of users on the Internet discuss a variety of topics on Question andAnswer (Q&A) instances. However, not all instances and topics receive the sameamount of attention, as some thrive and achieve self-sustaining levels ofactivity while others fail to attract users and either never grow beyond beinga small niche community or become inactive. Hence, it is imperative to not onlybetter understand but also to distill deciding factors and rules that defineand govern sustainable Q&A instances. We aim to empower community managers withquantitative methods for them to better understand, control and foster theircommunities, and thus contribute to making the Web a more efficient place toexchange information. To that end, we extract, model and cluster useractivity-based time series from 50 randomly selected Q&A instances from theStackExchange network to characterize user behavior. We find four distincttypes of user activity temporal patterns, which vary primarily according to theusers' activity frequency. Finally, by breaking down total activity in our 50Q&A instances by the previously identified user activity profiles, we classifythose 50 Q&A instances into three different activity profiles. Ourcategorization of Q&A instances aligns with the stage of development andmaturity of the underlying communities, which can potentially help operators ofsuch instances not only to quantitatively assess status and progress, but alsoallow them to optimize community building efforts.