2021
DOI: 10.1145/3479610
|View full text |Cite
|
Sign up to set email alerts
|

Disproportionate Removals and Differing Content Moderation Experiences for Conservative, Transgender, and Black Social Media Users: Marginalization and Moderation Gray Areas

Abstract: Transgender refers to people whose current gender is diferent than their gender assigned at birth, including non-binary trans people. We shorten transgender to "trans" for the remainder of this paper.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

2
24
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
5
2
1

Relationship

0
8

Authors

Journals

citations
Cited by 100 publications
(39 citation statements)
references
References 52 publications
(68 reference statements)
2
24
0
Order By: Relevance
“…This requires a much greater investment in good quality moderationsomething which even non-adult platforms currently struggle with -but which must be implemented if platforms are not to continue to marginalize the vulnerable. This issue in online sex work exactly mirrors the problems discussed in social media content moderation by Díaz and Hecht-Felella [148], Haimson et al [55], Schoenbeck et al [117] and many other scholars.…”
Section: Implications For Digital Experience and Designsupporting
confidence: 68%
“…This requires a much greater investment in good quality moderationsomething which even non-adult platforms currently struggle with -but which must be implemented if platforms are not to continue to marginalize the vulnerable. This issue in online sex work exactly mirrors the problems discussed in social media content moderation by Díaz and Hecht-Felella [148], Haimson et al [55], Schoenbeck et al [117] and many other scholars.…”
Section: Implications For Digital Experience and Designsupporting
confidence: 68%
“…Simpson and Semaan (2021) argued based on interviews with LGBTQ+ TikTok users that, while the platform did in some cases reaffirm their identities by showing them relevant personalized recommendations, the algorithms tended to promote normative representations of those identities, e.g., "mainstream" lesbian content. Oliver L. Haimson et al (2021b) found, based on user self-reports, that transgender users experienced disproportionately high levels of content removal, and Caplan and Gillespie (2020) referenced a number of cases in which LGBTQ+ users felt they had been targeted by YouTube's moderation algorithms because of their identities. Yet despite an extensive literature on conflicts, perhaps the most common form of interaction between users and platforms is a lack thereof.…”
Section: Despite the Relative Dearth Of Studies Specifically On Volun...mentioning
confidence: 99%
“…Though a very different problem, hate and harassment have proven similarly difficult for platforms to define in different contexts; language indicative of racism or homophobia in one context may have been co-opted to be humorous or even friendly when used within the targeted groups. While various platforms have attempted to find universal, contextagnostic responses to such problems, their attempts have consistently failed to achieve the desired results (Gillespie 2018;Oliver L. Haimson et al 2021b). Community-based platforms that rely on volunteer moderators can allow users some leeway to define these lines within their own communities, partially addressing the challenge of moderating content differently in different contexts.…”
mentioning
confidence: 99%
“…Cheney-Lippold (2011), on the other hand, speaks of the "soft power" of algorithms to refer to their influence on the existential possibilities of individuals. Many empirical pieces of research highlight the authority of algorithms in the fields in which they are applied (Haimson et al, 2021;Graham & Rodriguez, 2021;Gorwa et al, 2020;Campbell-Verduyn et al, 2017). Among these, we can mention Ma and Kou (2021) research in which emerges that the algorithm underlying the moderation of YouTube's content can orient not only the individual and collective action of YouTubers but also their feelings of insecurity and precariousness.…”
Section: Emerging Features Of Socio-digital Objectsmentioning
confidence: 99%