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

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.

Authors

Institutions

Publication Details

Journal
Law Technology and Humans
Published
2025-01-29
DOI
https://doi.org/10.5204/lthj.3730
Primary Topic
Recommender Systems and Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Joshua Krook
Law Technology and Humans
Recommender Systems and Techniques
article

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

Joshua Krook
article en

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.

Law Technology and Humans
University of Southampton (GB)
Openalex Percentile: Top 98%
Recommender Systems and Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.