My Algorithm: User Perceptions of Algorithmic Recommendations in Cultural Contexts

Abstract

Automated functions for discovery and recommendations are important features of all the major players in digital media and culture. This paper sets out to explore algorithms in cultural contexts via the users of these services, addressing the following research question: How do users relate to online automated discovery and recommendation services for cultural products and services? Departing from relevant literature and analyses of Twitter streams, the paper explores how users respond and relate to the automation of cultural discovery and recommendation with specific attention to perceived quality and relevance, along with evaluations of pressures on individual privacy. Preliminary findings indicate how active users seem to take a personal interest in the recommendation algorithms, seeing them as part of their online identities. Accordingly, we find users referring to an automated system for targeted recommendations as “my algorithm”.