Algorithmic Experts: Selling Algorithmic Lore on YouTube

被引:76
作者
Bishop, Sophie [1 ]
机构
[1] Kings Coll London, Dept Digital Humanities, London WC2R 2LS, England
来源
SOCIAL MEDIA + SOCIETY | 2020年 / 6卷 / 01期
关键词
algorithms; optimization; YouTube; INTERMEDIARIES;
D O I
10.1177/2056305119897323
中图分类号
G2 [信息与知识传播];
学科分类号
05 ; 0503 ;
摘要
This article considers the growing influence of self-styled algorithmic "experts." Experts build valuable brands, accumulate notoriety, and piece together careers by selling theorizations of algorithmic visibility on YouTube to aspiring and established creators. They function as intermediaries between sanctioned YouTube industries and the agency of cultural producers. Expertise is developed through research, strategies, and theories to help content creators mitigate platform-specific risks, particularly the risk of algorithmic invisibility. Experts develop entrepreneurial self-brands and position themselves as YouTube's adversaries, performing "experiments" ostensibly to reveal or translate hidden algorithmic signals or correct "misleading" information. However, ultimately, they teach creators to be complicit with YouTube's organizational strategies and business models. Studying algorithmic experts reveals insights into how new media producers negotiate platform visibility, but also speaks to long-standing questions about how the management of risk in cultural industries shapes symbolic production. I draw on a 3-year ethnography of YouTube industries to illustrate how experts interpret and instruct in how to become algorithmically (and advertiser) compliant on YouTube. In addition, I highlight their broader role as de facto producers and gatekeepers for aspiring and existing content producers. Meritocratic logic flows through experts' outputs-meaning expertise is limited to individualized and patchwork solutions that do not address the significant socio-economic inequalities that are still inherent on social media platforms.
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页数:11
相关论文
共 63 条
[1]   #familygoals: Family Influencers, Calibrated Amateurism, and Justifying Young Digital Labor [J].
Abidin, Crystal .
SOCIAL MEDIA + SOCIETY, 2017, 3 (02)
[2]  
[Anonymous], 2013, DISTINCTION SOCIAL C
[3]  
[Anonymous], 2015, The Black Box Society
[4]  
[Anonymous], 2018, ALGORITHMS OPPRESSIO, DOI [DOI 10.18574/NYU/9781479833641.001.0001, 10.18574/nyu/9781479833641.001.0001, DOI 10.2307/J.CTT1PWT9W5]
[5]   Baking Gender Into Social Media Design: How Platforms Shape Categories for Users and Advertisers [J].
Bivens, Rena ;
Haimson, Oliver L. .
SOCIAL MEDIA + SOCIETY, 2016, 2 (04)
[6]   CRITICAL QUESTIONS FOR BIG DATA Provocations for a cultural, technological, and scholarly phenomenon [J].
Boyd, Danah ;
Crawford, Kate .
INFORMATION COMMUNICATION & SOCIETY, 2012, 15 (05) :662-679
[7]  
Bucher J, 2018, STORYTELLING FOR VIRTUAL REALITY: METHODS AND PRINCIPLES FOR CRAFTING IMMERSIVE NARRATIVES, P141
[8]  
Bucher Taina., 2016, Innovative Methods in Media and Communication Research, P81, DOI DOI 10.1007/978-3-319-40700-5_5
[9]   Toy unboxing: living in a(n unregulated) material world [J].
Craig, David ;
Cunningham, Stuart .
MEDIA INTERNATIONAL AUSTRALIA, 2017, 163 (01) :77-86
[10]   Can an Algorithm be Agonistic? Ten Scenes from Life in Calculated Publics [J].
Crawford, Kate .
SCIENCE TECHNOLOGY & HUMAN VALUES, 2016, 41 (01) :77-92