Media Technologies - Essays on Communication, Materiality, and Society

By J. Söderberg. 2014

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016, background): “(Gillespie, 2012) The goal of this article was to look more deeply into machine learning algorithms and the nature of their ‘opacity’, relating this to sociological interests in classification and discrimination.”
Between Subjectivity and Imposition (2020, background): “Previous work has argued that data-driven systems are oen linked to “a technologically-inected promise of mechanical neutrality” [41].”
Anxiety, panic and self-optimization (2018, background): “…YouTube videos with ‘XXX, Porn’ to accrue traffic (Kessler and Schafer, 2009: 283), Facebook users tag their statuses with brands to push them up in algorithmic rankings (Gillespie, 2014), and Instagram users aspirationally copy and paste hashtags from their favourite influencers (Abidin, 2016).”
Algorithms and their others: Algorithmic culture in context (2016, background): “As Gillespie (2012) has noted, algorithms shift and evolve in deployment, particularly those hidden behind trade secrecy barriers; talking in any coherent way about ‘‘Google’s search term prediction’’ algorithm, for example, is deeply problematic given the invisible shifts in implementation and…”
Terms of inclusion: Data, discourse, violence (2020, unknown): “The landscape is further complicated by data processed algorithmically—that is, through processes and procedures of software that turn data inputs into particular outputs (Bucher, 2018; Gillespie, 2014).”
ORES (2019, unknown): “Algorithmic systems [94] play increasingly crucial roles in the governance of social processes [7, 26, 40].”
Recommended for you: The Netflix Prize and the production of algorithmic culture (2016, background): “And it is a story, finally, about tendencies toward the future, a future in which people and algorithms will continue to become ever more entangled in cultural production, both on and offline (Gillespie, 2014: 183–184).”
On Organizing Algorithms (2015, background): “The work of Gillespie (2013) and Introna (2013) suggest that alongside a recursive metaphor we could explore the following: conﬁguration through which users and/or clients are modelled and then encouraged to take up various positions in relation to the algorithm at work; com-modiﬁcation whereby the…”
Between autonomy and control: Strategies of arbitrage in the “on-demand” economy (2018, background): “…section illustrated on-demand companies’ strategies of arbitrage, which suggest a complex “entanglement” between the courier and the interface of algorithmic workforce management—“a recursive loop between the calculations of algorithms and the ‘calculations’ of people” (Gillespie, 2014: 183).”
Youth Perspectives on Critical Data Literacies (2017, background): “Although often more subtle and complex than described here, algorithmic discrimination has received significant attention among scholars [24] and in the popular press [31].”
Communicating Algorithmic Process in Online Behavioral Advertising (2018, background): “This has recently been called into question after researchers and activists have revealed biased, discriminatory, and privacyviolating algorithmic systems [19, 43, 46, 15].”
The platformization of cultural production: Theorizing the contingent cultural commodity (2018, unknown): “” This emerging algorithmic logic can be contrasted with the traditional “editorial logic,” which more explicitly relies on the “choices of experts” (Gillespie, 2014).”
Co-Writing with Opinionated Language Models Affects Users’ Views (2023, background): “Rather than mere technical platforms, algorithms become constitutive features of public life [47] that may change the political landscape [1].”
Understanding perception of algorithmic decisions: Fairness, trust, and emotion in response to algorithmic management (2018, background): “Our focus of inquiry—everyday people’s perceptions of algorithms—is closely related to recent discourses around socio-technical definitions of algorithms (Gillespie, 2014; Kitchin, 2016), which go beyond the technical, entitative definition described above.”
Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability (2018, background): “…in historical contexts, but they are also changing amid a new set of online cultures, digital infrastructures, and networked institutions defining the conditions under which systems can be seen and understood—conditions of visibility governed in part through algorithmic systems (Gillespie, 2014).”
How Platform-User Power Relations Shape Algorithmic Accountability: A Case Study of Instant Loan Platforms and Financially Stressed Users in India (2022, background): “and fairer decisions than their human counterparts [45, 52], they could also produce harmful outcomes, worsening inequality in society [20, 23, 50, 54, 92, 94, 98].”