Building Serendipity into Recommender Algorithms on Online Platforms: Reviving the Chaos and Randomness of the Early Internet Aesthetic

Abstract

Nostalgic comments about the early internet often praise its random, chaotic aesthetic. By contrast, the major platforms of today are typically viewed as corporate in aesthetic, with a one-size-fits-all profile and personalised recommendations of products. The curated life is the opposite of the serendipitous life. Instead of seeing strange or unusual items, online algorithms have been shown to trap users into ‘you loops’, surrounded by similar users in filter bubbles. Algorithms on major platforms give the illusion that users are getting what they want, yet users often complain of a form of aesthetic sameness, blandness and repetition regarding the products they see and are recommended.

In this article, we consider forms of resistance against algorithmic ranking and efficiency, including nostalgia for the early internet. This includes a consideration of early websites, which were more chaotic compared with the algorithmic ranking-based sites of today. We argue that the movement towards a curated life has resulted in a loss of serendipity for the user and a narrowing of the user experience, limiting personal growth and the variety of content to which users are exposed. This ‘narrowing’ effect contributes to a flattening of culture, where culture starts to reflect what the algorithm rewards. We consider ways to shift back to a more random aesthetic, where less-popular items are sometimes shown to the user to increase the serendipity they experience on major platforms.