Identifying Competition and Mutualism Between Online Groups
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2021
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| _version_ | 1866916511181963264 |
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| author | TeBlunthuis, Nathan Hill, Benjamin Mako |
| author_facet | TeBlunthuis, Nathan Hill, Benjamin Mako |
| contents | Platforms often host multiple online groups with overlapping topics and members. How can researchers and designers understand how related groups affect each other? Inspired by population ecology, prior research in social computing and human-computer interaction has studied related groups by correlating group size with degrees of overlap in content and membership, but has produced puzzling results: overlap is associated with competition in some contexts but with mutualism in others. We suggest that this inconsistency results from aggregating intergroup relationships into an overall environmental effect that obscures the diversity of competition and mutualism among related groups. Drawing on the framework of community ecology, we introduce a time-series method for inferring competition and mutualism. We then use this framework to inform a large-scale analysis of clusters of subreddits that all have high user overlap. We find that mutualism is more common than competition. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2107_06970 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | Identifying Competition and Mutualism Between Online Groups TeBlunthuis, Nathan Hill, Benjamin Mako Human-Computer Interaction Social and Information Networks Platforms often host multiple online groups with overlapping topics and members. How can researchers and designers understand how related groups affect each other? Inspired by population ecology, prior research in social computing and human-computer interaction has studied related groups by correlating group size with degrees of overlap in content and membership, but has produced puzzling results: overlap is associated with competition in some contexts but with mutualism in others. We suggest that this inconsistency results from aggregating intergroup relationships into an overall environmental effect that obscures the diversity of competition and mutualism among related groups. Drawing on the framework of community ecology, we introduce a time-series method for inferring competition and mutualism. We then use this framework to inform a large-scale analysis of clusters of subreddits that all have high user overlap. We find that mutualism is more common than competition. |
| title | Identifying Competition and Mutualism Between Online Groups |
| topic | Human-Computer Interaction Social and Information Networks |
| url | https://arxiv.org/abs/2107.06970 |