Historian Melvin Kranzberg once wrote that: “Technology is neither good nor bad; nor is it neutral”. That is, technology (digital techology, for instance) does more than allowing users to do something; the design of that techonological product actually encourages some behaviours, while discouraging (or, at least, downplaying) others. For instance, the addition of cameras to mobile phones changed the role of photos in our lives: photos stopped being commemoration items that memorialise key moments in our life, and became communication items that convey emotions, ideas or facts.
Social media platforms, too, change behaviour; and this paper by Cristina Alaimo and Jannis Kallinikos does a fascinating job of analysing how the design and user interface of a particular social media platform encourages consumers to engage in behaviour that support that platform’s business model. The paper is entitled “Computing the everyday: social media as data platforms”, and uses the case study of a social media community built around fashion.
Contrary to e-commerce platforms whose main source of revenues is the transactions performed on the website, social media communities are concerned with ‘the production, technological infrastructuring and, ultimately, trading of user profiles or tastes’ (p.17), which they then sell to retailers and brand owners.
In this particular case, the key source of revenue is insight into the community users’ fashion tastes and their intention to buy specific products or, as the paper’s authors say:
“The underlying motive is to transform shopping by uncovering new patterns, correlations or insights on user intention that precede buying actions and derive from social interaction data” (p.12).
Hence, the design of the platform encourages behaviours and emphasises activities that support that business model – from searching products, to following individual users and brands, and tagging. Tagging refers to the attachment of a bookmarklet to a product image (for instance, a pair of earrings from a particular brand or online store), and serves two purposes.
First, tagging signals an interest in the product. Tagging the picture is more intentional than browsing the brand’s website, or reading a magazine article. When calculating intention to buy, the social media platform owner scores tagging more highly than any other activity performed on the platform, leading to a calculation of which users are more or less explicitly interested in the product.
Second, a tag that is retagged by other users gives an indication of the item’s popularity:
“Popularity obtained by computing retags is taken as a good measure of the social approval of products and users alike. (…) A popular product is a product that has more possibilities of being seen and thus bought” (p. 12)
The authors go on to show how:
“tagging and following constitute the key platform data-generating actions whereas clicking, searching, and browsing are less fundamental but still important actions that complement and variously qualify the data provided by tagging and following’ (p. 16).
And, therefore ‘tagging is designed to be the spine of (this particular) platform’ (p.16), as opposed to features that might be most prevalent on other types of social media communities or websites, such as editorial recommendations, product reviews or magazine articles.
This paper shows how social media companies design their platforms in order to engineer the behaviours that support their business models. This may not be a revolutionary insight, but it is a crucial and humbling one for those of us that rely on social media platforms to work, stay in touch with the world, and express our creativity.
Ana Canhoto 