Online knowledge communities form around a vast number of topics, but not all of them thrive and achieve self-sustaining numbers of users and levels of activity. Since these online communities are ubiquitous, large knowledge repositories and up-to-date news sources, it is important to better understand and support activity and growth on these platforms. To that end, I will distill and learn more about key factors that drive and define success and failure of these communities and to devise stochastic dynamical models for their lifecycle stages as a product of the interactions between their members. With this approach, I will be able to partially predict the future evolution of a given online community. Having these newly gained insights, it will be possible to measure and quantify critical differences in dynamics between successful and failing online knowledge communities, thus helping community managers to quantitatively assess the status of their communities and steer them towards self-sustainable activity levels. My backhground in Mathematics, Economics and Computer Science, combined with my preliminary research experience in characterizing activity dynamics of online communities puts me in an unique position to tackle the challenges outlined in this PhD proposal.
|Effective start/end date||1/03/19 → 28/02/22|
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