Bots, bespoke, code and the materiality of software platforms

By R. Stuart Geiger. 2014

120 citations recorded by the source corpus.

Subfields: Communication, Computer Science Applications, Sociology and Political Science

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Citations in the corpus

Towards Algorithmic Experience: Initial Efforts for Social Media Contexts (2018, background): “Geiger argues that those who have the power to decide, write or design what is executed in code, also have the power to regulate the behaviors and opinions that algorithms entice [13:351–352].”
Transparent to whom? No algorithmic accountability without a critical audience (2018, background): “Algorithmic models cannot be separated from the practices in which they are designed, programmed, and used (Geiger, 2014).”
ORES (2019, background): “ses that were designed over a decade ago remain largely unchanged [21]. Wikipedian tool developers play a critical role in the larger conversation of how the community should be doing quality control [11, 21]. There are few formal barriers to anyone auditing, modifying, or developing their own class”
Flexibility in the Gig Economy: Managing Time on Three Online Piecework Platforms (2018, unknown): “We saw that some workers used their own technologies or ‘bespoke code’ (Geiger 2014) to attempt to alter the rules of the game.”
Algorithmic content moderation: Technical and political challenges in the automation of platform governance (2020, background): “Later, as large scale peer-production communities like Wikipedia grew rapidly, automated ‘bot’ moderators enforced Wikipedia’s rules, fought vandalism and monitored articles slated for deletion, playing a key role in the moderation process (Geiger, 2014).”
The limits of crisis data: analytical and ethical challenges of using social and mobile data to understand disasters (2015, background): “Those bots are also friending and retweeting other bots, producing a complex bot culture which is an emerging phenomenon unto itself (for discussions of bot activity in the context of Wikipedia, see Geiger and Ribes 2010; Geiger 2011, 2014; Van Dijck 2013: 137–140).”
Thinking critically about and researching algorithms (2014, methodology): “…forms: a detailed case study of a single algorithm, or class of algorithms, to examine the nature of algorithms more generally (e.g., Bucher, 2012; Geiger, 2014; Mackenzie, 2007; Montfort et al., 2012); a detailed examination of the use of algorithms in one domain, such as journalism (Anderson,…”