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Lookup NU author(s): Flavio Primo, Emeritus Professor Alexander RomanovskyORCiD, Professor Paolo MissierORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Substantial research is available on detecting in influencers on socialmedia platforms. In contrast, comparatively few studies exists on therole of online activists, defined informally as users who actively participatein socially-minded online campaigns. Automatically discovering activists whocan potentially be approached by organisations that promote social campaignsis important, but not easy, as they are typically active only locally, and, unlikeinuencers, they are not central to large social media networks. We make thehypothesis that such interesting users can be found on Twitter within temporallyand spatially localised contexts. We dene these as small but topicalfragments of the network, containing interactions about social events or campaignswith a signicant online footprint. To explore this hypothesis, we havedesigned an iterative discovery pipeline consisting of two alternating phases ofuser discovery and context discovery. Multiple iterations of the pipeline resultin a growing dataset of user proles for activists, as well as growing set ofonline social contexts. This mode of exploration differs significantly from priortechniques that focus on in influencers, and presents unique challenges because ofthe weak online signal available to detect activists. The paper describes the designand implementation of the pipeline as a customisable software framework,where user-defined operational definition of online activism can be explored.We present an empirical evaluation on two extensive case studies, one concerninghealthcare-related campaigns in the UK during 2018, the other related toonline activism in Italy during the COVID-19 pandemic.
Author(s): Primo F, Romanovsky A, de Mello R, Garcia A, Missier P
Publication type: Article
Publication status: Published
Journal: World Wide Web: Internet and Web Information Systems
Year: 2021
Volume: 24
Pages: 1235–1271
Print publication date: 01/07/2021
Online publication date: 11/06/2021
Acceptance date: 26/04/2021
Date deposited: 26/04/2021
ISSN (print): 1386-145X
ISSN (electronic): 1573-1413
Publisher: Springer
URL: https://doi.org/10.1007/s11280-021-00887-2
DOI: 10.1007/s11280-021-00887-2
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