Navigational, Informational or Punk-Rock? An Exploration of Search Intent in the Musical Domain

The search engine of music streaming platforms is a high-control
method for navigating the catalog. If one is to study users’ search
behavior in this context, one can leverage the vast body of research
on general information behavior while challenging previously well
validated models with the domain-specific differences. Due to the
nature of musical content, users present a series of different needs
and behaviors than on traditional web search. For instance, some
users employ the search engine as a means to drive their listening
session, inputting many queries in close succession not related to
the same information goal.

In this paper, we investigate users’ search goals and how they
modulate information behavior in the context of streaming platforms. To this end, we explore real search sessions of users looking
for musical content in the context of a major streaming service.
We introduce a data-driven method for identifying classes of information needs by aggregating both low-level activity patterns
and relative query specificity. We show that, when combined, these
features provide an approach not only for isolating classes of user
search intent, but for understanding human-music relationship as
a whole.

This paper has been accepted for publication in the proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2022).