Creating students’ algorithmic selves: shedding light on social media’s representational affordances
Abstract
This article presents and analyses the results of focus group studies conducted with students at an international university in Lithuania, interpreting the results in light of the extant literature on social media’s impact on the creation and performance of the self. The authors reveal a mixed picture whereby the respondents seem to demonstrate an unexpectedly casual and cynical attitude towards social media while, upon closer inspection, still remaining part of social media’s productive exchanges, contributing their data and attention in return for satisfaction. Hence, while by no means rejecting the standard interpretation provided in mainstream literature, the authors are able to present a more complex and nuanced picture of young people’s attitudes towards and interaction with social media and the self-creation affordances thereof, ultimately a close, constitutive, and creative interrelationship between humans and code.
Article in English.
Studentų algoritminių savasčių kūrimas: socialinių medijų reprezentacinių galimybių tyrimas
Santrauka
Šiame straipsnyje pristatomi ir analizuojami rezultatai, gauti iš tikslinių grupių interviu su Lietuvoje esančio tarptautinio universiteto studentais. Šie rezultatai interpretuojami literatūros, aptariančios socialinių medijų poveikį savęs kūrimui ir raiškai, kontekste. Autoriai atskleidžia prieštaringą paveikslą – respondentai demonstruoja netikėtai atsainų ir net cinišką požiūrį į socialines medijas, tačiau, pažvelgus giliau, vis vien išlieka socialinių medijų produkcijos santykių dalimi, atiduodami savo duomenis mainais į pasitenkinimą. Tad, nors ir neatmesdami literatūroje dominuojančio požiūrio, autoriai pristato sudėtingesnį ir labiau niuansuotą požiūrį į jaunų žmonių nuomonę apie socialines medijas bei jų poveikį savęs kūrimui. Tokiu būdu parodomas atviras ir kūrybiškas santykis tarp žmogiškųjų aktorių ir programinio kodo.
Reikšminiai žodžiai: savastys, aglomeracija, algoritmas, dėmesys, duomenys, savikūra, socialinės medijos
Keyword : affordances, agglomeration, algorithm, attention, data, self-creation, social media
How to Cite
Kalpokas, I., Sabaliauskaitė, E., & Pegushina, V. (2020). Creating students’ algorithmic selves: shedding light on social media’s representational affordances. Creativity Studies, 13(2), 292-307. https://doi.org/10.3846/cs.2020.10803
This work is licensed under a Creative Commons Attribution 4.0 International License.
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Carlson, M. (2018). Automating judgment? Algorithmic judgment, news knowledge, and journalistic professionalism. New Media and Society, 20(5), 1755–1772. https://doi.org/10.1177/1461444817706684
Choat, S. (2018). Science, agency and ontology: A historical-materialist response to new materialism. Political Studies, 66(4), 1027–1042. https://doi.org/10.1177/0032321717731926
Citton, Y. (2017). The ecology of attention. Polity Press.
Cotter, K. (2019). Playing the visibility game: How digital influencers and algorithms negotiate influence on Instagram. New Media and Society, 21(4), 895–913. https://doi.org/10.1177/1461444818815684
Cover, R. (2016). Digital identities: Creating and communicating the online self. Elsevier Inc.
Danaher, J., Hogan, M. J., Noone, Ch., Kennedy, R., Behan, A., Paor, De A., Felzmann, H., Haklay, M., Khoo, S.-M., Morison, J., Murphy, M. H., O’Brolchain, N., Schafer, B., & Shankar, K. (2017). Algorithmic governance: Developing a research agenda through the power of collective intelligence. Big Data and Society, 4(2), 1–21. https://doi.org/10.1177/2053951717726554
Dourish, P. (2016). Algorithms and their others: Algorithmic culture in context. Big Data and Society, 3(2)1–11. https://doi.org/10.1177/2053951716665128
Faraj, S., Pachidi, S., & Sayegh, K. (2018). Working and organizing in the age of the learning algorithm. Information and Organization, 28(1), 62–70. https://doi.org/10.1016/j.infoandorg.2018.02.005
Flyverbom, M., & Murray, J. (2018). Datastructuring: Organizing and curating digital traces into action. Big Data and Society, 5(2), 1–12. https://doi.org/10.1177/2053951718799114
Goodwin, I., Griffin, Ch., Lyons, A., McCreanor, T., & Moewaka Barnes, H. (2016). Precarious popularity: Facebook drinking photos, the attention economy, and the regime of the branded self. Social Media + Society, 2(1), 1–13. https://doi.org/10.1177/2056305116628889
Just, N., & Latzer, M. (2017). Governance by algorithms: Reality construction by algorithmic selection on the internet. Media, Culture and Society, 39(2), 238–258. https://doi.org/10.1177/0163443716643157
Kelleher, J. D., & Tierney, B. (2018). Data science. Series: The MIT Press Essential Knowledge. Massachusetts Institute of Technology. https://doi.org/10.7551/mitpress/11140.001.0001
Klinger, U., & Svensson, J. (2018). The end of media logics? On algorithms and agency. New Media and Society, 20(12), 4653–4670. https://doi.org/10.1177/1461444818779750
Langlois, G., & Elmer, G. (2019). Impersonal subjectivation from platforms to infrastructures. Media, Culture and Society, 41(2), 236–251. https://doi.org/10.1177/0163443718818374
Lee, M. K. (2018). Understanding perception of algorithmic decisions: Fairness, trust, and emotion in response to algorithmic management. Big Data and Society, 5(1), 1–16. https://doi.org/10.1177/2053951718756684
Pasquale, F. (2015). The Black Box Society: The secret algorithms that control money and information. President and Fellows of Harvard College. https://doi.org/10.4159/harvard.9780674736061
Pink, S., Sumartojo, Sh., Lupton, D., & Heyes La Bond, Ch. (2017). Mundane data: The routines, contingencies and accomplishments of digital living. Big Data and Society, 4(1), 1–12. https://doi.org/10.1177/2053951717700924
Pötzsch, H. (2018). Archives and identity in the context of social media and algorithmic analytics: Towards an understanding of iArchive and predictive retention. New Media and Society, 20(9), 3304–3322. https://doi.org/10.1177/1461444817748483
Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5), 1–6. https://doi.org/10.1108/10748120110424816
Shi, Y., Luo, Y. L. L., Liu, Y., & Yang, Z. (2019). Affective experience on social networking sites predicts psychological well-being off-line. Psychological Reports, 122(5), 1666–1677. https://doi.org/10.1177/0033294118789039
Srnicek, N. (2017). Platform capitalism. Polity Press.
Vaidhyanathan, S. (2018). Anti-social media: How facebook disconnects us and undermines democracy. Oxford University Press.
Weber, R. H. (2018). “Rose is a rose is a rose is a rose” – What about code and law? Computer Law and Security Review, 34(4), 701–706. https://doi.org/10.1016/j.clsr.2018.05.005
Webster, J. G. (2017). Three myths of digital media. Convergence: The International Journal of Research into New Media Technologies, 23(4), 352–361. https://doi.org/10.1177/1354856517700385
Yeung, K. (2017). “Hypernudge”: Big Data as a mode of regulation by design. Information, Communication and Society, 20(1), 118–136. https://doi.org/10.1080/1369118X.2016.1186713