# Are All Successful Communities Alike? Characterizing and Predicting the Success of Online Communities

## TL;DR

This study explores multiple success metrics for online communities, revealing they are distinct and can be predicted by different early behaviors, emphasizing success as a multi-dimensional concept.

## Contribution

It systematically analyzes various success measures and demonstrates their independence and predictability from community properties and early behaviors.

## Key findings

- Success measures are weakly correlated, indicating different success types.
- Different community attributes predict different success metrics.
- Success in online communities is multi-faceted and cannot be captured by a single measure.

## 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.