TY - JOUR
T1 - Investigating Characteristics of Media Recommendation Solicitation in r/ifyoulikeblank
AU - Bhuiyan, Md Momen
AU - Hu, Donghan
AU - Jelson, Andrew
AU - Mitra, Tanushree
AU - Lee, Sang Won
N1 - Publisher Copyright:
© 2024 Owner/Author.
PY - 2024/11/8
Y1 - 2024/11/8
N2 - 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.
AB - 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.
KW - content analysis
KW - crowdsourcing recommendation
KW - feature selection
KW - ifyoulikeblank
KW - information seeking
UR - http://www.scopus.com/inward/record.url?scp=85209409150&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85209409150&partnerID=8YFLogxK
U2 - 10.1145/3687041
DO - 10.1145/3687041
M3 - Article
AN - SCOPUS:85209409150
SN - 2573-0142
VL - 8
JO - Proceedings of the ACM on Human-Computer Interaction
JF - Proceedings of the ACM on Human-Computer Interaction
IS - CSCW2
M1 - 502
ER -