Are All Successful Communities Alike? Characterizing and Predicting the Success of Online Communities
March 18, 2019 ยท Declared Dead ยท ๐ The Web Conference
"No code URL or promise found in abstract"
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Authors
Tiago Cunha, David Jurgens, Chenhao Tan, Daniel Romero
arXiv ID
1903.07724
Category
cs.SI: Social & Info Networks
Cross-listed
cs.CY
Citations
42
Venue
The Web Conference
Last Checked
3 months ago
Abstract
The proliferation of online communities has created exciting opportunities to study the mechanisms that explain group success. While a growing body of research investigates community success through a single measure -- typically, the number of members -- we argue that there are multiple ways of measuring success. Here, we present a systematic study to understand the relations between these success definitions and test how well they can be predicted based on community properties and behaviors from the earliest period of a community's lifetime. We identify four success measures that are desirable for most communities: (i) growth in the number of members; (ii) retention of members; (iii) long term survival of the community; and (iv) volume of activities within the community. Surprisingly, we find that our measures do not exhibit very high correlations, suggesting that they capture different types of success. Additionally, we find that different success measures are predicted by different attributes of online communities, suggesting that success can be achieved through different behaviors. Our work sheds light on the basic understanding of what success represents in online communities and what predicts it. Our results suggest that success is multi-faceted and cannot be measured nor predicted by a single measurement. This insight has practical implications for the creation of new online communities and the design of platforms that facilitate such communities.
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