arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2408.06201cs.HCcs.IR
收藏

调查 r/ifyoulikeblank 中媒体推荐征求的特征

Investigating Characteristics of Media Recommendation Solicitation in r/ifyoulikeblank

Md Momen Bhuiyan, Donghan Hu, Andrew Jelson, Tanushree Mitra, Sang Won Lee

AI总结:

本文通过定性分析 r/ifyoulikeblank 的帖子,揭示用户寻求众包媒体推荐的原因、查询中的新颖信息及互动细化模式,为智能推荐系统设计提供启示。

摘要:

尽管存在 Google、Netflix 和 Spotify 等基于搜索的推荐系统,在线用户有时仍会转向 r/ifyoulikeblank subreddit 等场所寻求众包推荐。在这项探索性研究中,我们探究用户为何前往 r/ifyoulikeblank、他们如何寻找推荐,以及该 subreddit 的用户如何回应推荐请求。为回答这些问题,我们收集了 r/ifyoulikeblank 的样本帖子,并采用定性方法进行分析。分析表明,用户出于多种原因来到该 subreddit,例如热门搜索系统已被用尽、不知道要搜索什么条目或如何搜索,以及认为人群比搜索系统拥有更好的知识。通过考察用户的查询及其描述,我们发现了用户在使用 r/ifyoulikeblank 寻求推荐时提供的新颖信息。例如,他们有时会根据用于创作作品的工具来请求作品推荐;或者,表明推荐寻求者的时间限制有时有助于使推荐更贴合其需求。最后,推荐回复与互动揭示了请求者和回复者如何细化查询与推荐的模式。我们的工作为未来智能推荐系统的设计提供了参考。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑