Algorithmisation

Aleksandra Krstic, University of Belgrade, Serbia
aleksandrass@yahoo.com

Algorithmisation refers to designing and defining a series of steps or instructions to solve a problem or perform a task. It is most often associated with the performance of breaking down a problem into smaller, more manageable parts and creating a set of procedures that a computer or a human can follow in order to achieve a specific goal. In computer science and programming, algorithms are sets of rules used to solve problems or perform computations. In social media, algorithms are used to sort endless content, determine how content is filtered, ranked, selected, matched to audiences with similar preferences, and recommended to users. The algorithmisation process is often seen to bring order in different data cultures by reducing their complexity. In academic scholarship, therefore, algorithms are seen as ‘the metaphor of modern culture’, especially in the context of information abundance, noise, and overload, where various information selection strategies, such as filtering on social media, work to direct feeds, control preferences, and drive social media experiences. There are many forms of algorithmisation, such as the Big Data model, data visualisation model, and others that work effectively for the purpose of data gathering and advertising. In comparison to other social media platforms, authors highlight TikTok as the most algorithm-centered one, because it has been particularly known for its explicit and unprecedented use of the ‘for you’ algorithm, which determines the users’ exposure to content. Algorithms drive users through overabundance of posts and endless content online, have control over what users see and get, connect them with others who like similar things, and recommend further exploration of data based on users’ behaviour.

Keywords: algorithm, algorithmisation, media

Related Entries: Audience, Data/Dataset, Computational Linguistics

References:
García-Orosa, B., Canavilhas, J., & Vázquez-Herrero, J. (2023). Algorithms and communication: A systematized literature review. Comunicar, 74(31): 9-21. https://doi.org/10.3916/C74-2023-01
Just, N, & Latzer, M. (2017). Governance by algorithms: reality construction by algorithmic selection on the Internet. Media, Culture & Society, 39(2) 238–258.
Nielsen, S. B., Rinaldi, F. M., & Petersson, G. J. (Eds.). (2025). Artificial Intelligence and evaluation: Emerging technologies and their implications for evaluation. Routledge.
Schellewald, A. (2022). Theorizing “stories about algorithms” as a mechanism in the formation and maintenance of algorithmic imaginaries. Social Media + Society, 8(1),1–10.