54 lines
6.3 KiB
BibTeX
54 lines
6.3 KiB
BibTeX
@article{cavaDriversSocialInfluence2023,
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title = {Drivers of Social Influence in the {{Twitter}} Migration to {{Mastodon}}},
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author = {Cava, Lucio La and Aiello, Luca Maria and Tagarelli, Andrea},
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year = {2023},
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month = dec,
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journal = {Scientific Reports},
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volume = {13},
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number = {1},
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pages = {21626},
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issn = {2045-2322},
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doi = {10.1038/s41598-023-48200-7},
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urldate = {2024-02-02},
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abstract = {The migration of Twitter users to Mastodon following Elon Musk's acquisition presents a unique opportunity to study collective behavior and gain insights into the drivers of coordinated behavior in online media. We analyzed the social network and the public conversations of about 75,000 migrated users and observed that the temporal trace of their migrations is compatible with a phenomenon of social influence, as described by a compartmental epidemic model of information diffusion. Drawing from prior research on behavioral change, we delved into the factors that account for variations of the effectiveness of the influence process across different Twitter communities. Communities in which the influence process unfolded more rapidly exhibit lower density of social connections, higher levels of signaled commitment to migrating, and more emphasis on shared identity and exchange of factual knowledge in the community discussion. These factors account collectively for 57\% of the variance in the observed data. Our results highlight the joint importance of network structure, commitment, and psycho-linguistic aspects of social interactions in characterizing grassroots collective action, and contribute to deepen our understanding of the mechanisms that drive processes of behavior change of online groups.},
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langid = {english}
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}
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@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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@article{newellUserMigrationOnline,
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title = {User {{Migration}} in {{Online Social Networks}}: {{A Case Study}} on {{Reddit During}} a {{Period}} of {{Community Unrest}}},
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author = {Newell, Edward and Jurgens, David and Saleem, Haji Mohammad and Vala, Hardik and Sassine, Jad and Armstrong, Caitrin and Ruths, Derek},
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pages = {10},
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abstract = {Platforms like Reddit have attracted large and vibrant communities, but the individuals in those communities are free to migrate to other platforms at any time. History has borne this out with the mass migration from Slashdot to Digg. The underlying motivations of individuals who migrate between platforms, and the conditions that favor migration online are not well-understood. We examine Reddit during a period of community unrest affecting millions of users in the summer of 2015, and analyze large-scale changes in user behavior and migration patterns to Reddit-like alternative platforms. Using self-reported statements from user comments, surveys, and a computational analysis of the activity of users with accounts on multiple platforms, we identify the primary motivations driving user migration. While a notable number of Reddit users left for other platforms, we found that an important pull factor that enabled Reddit to retain users was its long tail of niche content. Other platforms may reach critical mass to support popular or ``mainstream'' topics, but Reddit's large userbase provides a key advantage in supporting niche topics.},
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langid = {english}
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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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