30 lines
3.1 KiB
BibTeX
30 lines
3.1 KiB
BibTeX
@article{fieslerMovingLandsOnline2020,
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title = {Moving across Lands: Online Platform Migration in Fandom Communities},
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shorttitle = {Moving across Lands},
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author = {Fiesler, Casey and Dym, Brianna},
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year = {2020},
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month = may,
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journal = {Proc. ACM Hum.-Comput. Interact},
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volume = {4},
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number = {CSCW1},
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pages = {042:1--042:25},
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doi = {10.1145/3392847},
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urldate = {2020-06-27},
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abstract = {When online platforms rise and fall, sometimes communities fade away, and sometimes they pack their bags and relocate to a new home. To explore the causes and effects of online community migration, we examine transformative fandom, a longstanding, technology-agnostic community surrounding the creation, sharing, and discussion of creative works based on existing media. For over three decades, community members have left and joined many different online spaces, from Usenet to Tumblr to platforms of their own design. Through analysis of 28 in-depth interviews and 1,886 survey responses from fandom participants, we traced these migrations, the reasons behind them, and their impact on the community. Our findings highlight catalysts for migration that provide insights into factors that contribute to success and failure of platforms, including issues surrounding policy, design, and community. Further insights into the disruptive consequences of migrations (such as social fragmentation and lost content) suggest ways that platforms might both support commitment and better support migration when it occurs.}
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}
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@inproceedings{teblunthuisIdentifyingCompetitionMutualism2022,
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title = {Identifying Competition and Mutualism between Online Groups},
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booktitle = {International {{AAAI Conference}} on {{Web}} and {{Social Media}} ({{ICWSM}} 2022)},
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author = {TeBlunthuis, Nathan and Hill, Benjamin Mako},
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year = {2022},
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month = jun,
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volume = {16},
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pages = {993--1004},
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publisher = {{AAAI}},
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address = {{Atlanta, Georgia, USA}},
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urldate = {2021-07-16},
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abstract = {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.},
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keywords = {Computer Science - Human-Computer Interaction,Computer Science - Social and Information Networks}
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}
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