Investigating Characteristics of Media Recommendation Solicitation in r/ifyoulikeblank

TL;DR

This study explores why users seek crowd-based recommendations on r/ifyoulikeblank, analyzing their motivations, query characteristics, and interaction patterns to inform future recommender system design.

Contribution

It provides a qualitative analysis of user motivations, query features, and interaction patterns in a crowdsourced recommendation subreddit, revealing novel user behaviors.

Findings

Users seek recommendations after exhausting search engines.

Users provide detailed contextual information in requests.

Interaction patterns show iterative query refinement.

Abstract

Despite the existence of search-based recommender systems like Google, Netflix, and Spotify, online users sometimes may turn to crowdsourced recommendations in places like the r/ifyoulikeblank subreddit. In this exploratory study, we probe why users go to r/ifyoulikeblank, how they look for recommendation, and how the subreddit users respond to recommendation requests. To answer, we collected sample posts from r/ifyoulikeblank and analyzed them using a qualitative approach. Our analysis reveals that users come to this subreddit for various reasons, such as exhausting popular search systems, not knowing what or how to search for an item, and thinking crowd have better knowledge than search systems. Examining users query and their description, we found novel information users provide during recommendation seeking using r/ifyoulikeblank. For example, sometimes they ask for artifacts recommendation based on the tools used to create them. Or, sometimes indicating a recommendation seeker's time constraints can help better suit recommendations to their needs. Finally, recommendation responses and interactions revealed patterns of how requesters and responders refine queries and recommendations. Our work informs future intelligent recommender systems design.