Automated Trouble: The Role of Algorithmic Selection in Harms on Social Media Platforms

Abstract

Social media platforms like Facebook, YouTube, and Twitter have become major objects of criticism for reasons such as privacy violations, anticompetitive practices, and interference in public elections. Some of these problems have been associated with algorithms, but the roles that algorithms play in the emergence of different harms have not yet been systematically explored. This article contributes to closing this research gap with an investigation of the link between algorithms and harms on social media platforms. Evidence of harms involving social media algorithms was collected from media reports and academic papers within a two-year timeframe from 2018 to 2019, covering Facebook, YouTube, Instagram, and Twitter. Harms with similar casual mechanisms were grouped together to inductively develop a typology of algorithmic harm based on the mechanisms involved in their emergence: (1) algorithmic errors, undesirable, or disturbing selections; (2) manipulation by users to achieve algorithmic outputs to harass other users or disrupt public discourse; (3) algorithmic reinforcement of pre-existing harms and inequalities in society; (4) enablement of harmful practices that are opaque and discriminatory; and (5) strengthening of platform power over users, markets, and society. Although the analysis emphasizes the role of algorithms as a cause of online harms, it also demonstrates that harms do not arise from the application of algorithms alone. Instead, harms can be best conceived of as socio-technical assemblages, composed of the use and design of algorithms, platform design, commercial interests, social practices, and context. The article concludes with reflections on possible governance interventions in response to identified socio-technical mechanisms of harm. Notably, while algorithmic errors may be fixed by platforms themselves, growing platform power calls for external oversight.

On following and becoming a follower

“…News articles about these scandals and each YouTuber's responses have been popping up in my Facebook feed as recommended content; while I have been following these YouTubers around, my online activity now means that they are now following me around. These algorithmically controlled social networks use data from my online activity to create a profile of my personality, needs, and interests, which they use to recommend content to me as a follower (Arthurs et al, 2018;Bucher, 2018;Saurwein & Spencer-Smith, 2021). As my algorithmic affect loop slowly encapsulated other social media platforms, it changed how and what I related to, what I knew about each YouTuber, and what I trusted.…”

“…Algorithms are machine-learning programs that use data to predict future online behaviors (Gillespie, 2014). Social media platforms such as YouTube use algorithms to curate, recommend, and moderate content as well as advertising (Saurwein & Spencer-Smith, 2021). Algorithmic data is presented as value-neutral but retains the biases of its human creators, shaping not only the viewing patterns of online users but also their visibility and humanity (Benjamin, 2019).…”

Algorithms of Social Media for Science Education to Cybercrime Reduced

“…The social media sites create unique algorithms for every person who uses the site which means no two people will have the exact same social media news feed. Essentially, social media algorithms analyze user behavior and prioritize content the platform believes the user wants to see and is most likely to engage (Guess et al, 2023;Reviglio & Agosti, 2020;Saurwein & Spencer-Smith, 2021).…”

When the bridge is not human: Algorithmic interference in forming social relationships through the manipulation of weak ties

“…By 2024, an estimated 276.9 million adults worldwide will be using a dating app (Statista, 2022); in the US, 40% of the adult population has used a dating app or website (Hosanagar, 2019). The shift in ad spending allocated to reaching consumers on these sites demonstrates that companies recognize the value of social media in users' lives and attempt to capitalize on it (Saurwein & Spencer-Smith, 2021).…”