Platforms often host multiple online groups with highly overlapping topics and members. How can researchers and designers understand how interactions between related groups affect measures of group health? Inspired by population ecology, prior social computing research has studied competition and mutualism among related groups by correlating group size with degrees of overlap in content and membership. The resulting body of evidence is puzzling as overlaps seem sometimes to help and other times to hurt. We suggest that this confusion results from aggregating inter-group relationships into an overall environmental effect instead of focusing on networks of competition and mutualism among groups. We propose a theoretical framework based on community ecology and a method for inferring competitive and mutualistic interactions from time series participation data. We compare population and community ecology analyses of online community growth by analyzing clusters of subreddits with high user overlap but varying degrees of competition and mutualism.

翻译：研究人员和设计者如何理解相关群体之间的互动如何影响群体健康衡量标准?受人口生态学的启发,先前的社会计算研究通过将群体规模与内容和成员的重叠程度联系起来,研究了相关群体之间的竞争和相互性。由此得出的大量证据令人费解,因为重叠有时似乎有帮助,有时还会伤害其他时间。我们建议,这种混淆的结果是将群体间的关系整合成一个整体环境影响,而不是侧重于群体间的竞争和相互性关系网络。我们提出了一个理论框架,以社区生态为基础,并用时间序列参与数据推断竞争性和相互性的互动。我们通过分析用户高度重叠但竞争和相互性程度不同的子编辑群,对在线社区增长的人口和社区生态分析进行比较。