2020
DOI: 10.1177/1350508420961532
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Activists in the dark: Social media algorithms and collective action in two social movement organizations

Abstract: It is widely established that social media afford social movement (SM) organizations new ways of organizing. Critical studies point out, however, that social media use may also trigger negative repercussions due to the commercial interests that are designed into these technologies. Yet empirical evidence about these matters is scarce. In this article, we investigate how social media algorithms influence activists’ actualization of collective affordances. Empirically, we build on an ethnographic study of two SM… Show more

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Cited by 53 publications
(63 citation statements)
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“…Another theme that relates to the submissions of this special issue is how technology hinders or counter-acts efforts at digital activism and new forms of organizing. Etter and Albu (2021) conduct case studies on social movement organizations in Tunisia to explore the effects of social media algorithms on the ways social movements organize. The authors identify the negative effects of social media due to the economic logics that are designed into these systems and that affect activist’s affordances.…”
Section: Contributions Of the Special Issue And Avenues For Future Rementioning
confidence: 99%
See 1 more Smart Citation
“…Another theme that relates to the submissions of this special issue is how technology hinders or counter-acts efforts at digital activism and new forms of organizing. Etter and Albu (2021) conduct case studies on social movement organizations in Tunisia to explore the effects of social media algorithms on the ways social movements organize. The authors identify the negative effects of social media due to the economic logics that are designed into these systems and that affect activist’s affordances.…”
Section: Contributions Of the Special Issue And Avenues For Future Rementioning
confidence: 99%
“…In this sense, the digitally enabled public arena of citizenship is distorted as the underlying technologies are not designed to facilitate a public discourse, but to attract the attention of users by curating the content that they are exposed to in a way that it serves the interests of those commercial or political actors who buy access and data from the social media firms. The study by Etter and Albu (2021) thus provides an important empirical underpinning for how commercial and political interests clash, and the resulting negative implications are for digital activism, new forms of organizing, but also society in general. Future research could study more carefully how the underlying commercial logic of different tech firms shapes the different public arenas of citizenship they construct, and the types of digital activism and collective organization they enable (Whelan et al, 2013).…”
Section: Contributions Of the Special Issue And Avenues For Future Rementioning
confidence: 99%
“…These communities of themselves fall a long way short of being vehicles for mobilisation (Ford and Honan, 2019). They do have the potential as 'seed beds' for organising activity among workers who are otherwise isolated from one another (Maffie, 2020); however, the fragmented nature of online communities has also been seen as an impediment to building the necessary trust and solidarity for collective action (Wood et al, 2018) in part due to their own commercial orientation (Etter and Albu, 2021).…”
Section: Voice In the Gig Economymentioning
confidence: 99%
“…As processes of digitalization and automation of communicative practices continue to gain traction, ascertaining the communicative effects of algorithms, especially pertaining to the organization of social media platforms (Etter and Abu, 2021; Leonardi and Vaast, 2017), has become a main concern of communication studies. Today, algorithms not only set the scene for human communication by producing new media logics (Klinger and Svensson, 2018) but increasingly order, influence and even take over communicative tasks (Wiesenberg et al., 2017; Zerfass et al., 2020).…”
Section: Conceptualizing Algorithmsmentioning
confidence: 99%