Recommender systems have become a ubiquitous part of modern web applications. They help users discover new and relevant items. Today's users, through years of interaction with these systems have developed an inherent understanding of how recommender systems function, what their objectives are, and how the user might manipulate them. We describe this understanding as the Theory of the Recommender. In this study, we conducted semi-structured interviews with forty recommender system users to empirically explore the relevant factors influencing user behavior. Our findings, based on a rigorous thematic analysis of the collected data, suggest that users possess an intuitive and sophisticated understanding of the recommender system's behavior. We also found that users, based upon their understanding, attitude, and intentions change their interactions to evoke desired recommender behavior. Finally, we discuss the potential implications of such user behavior on recommendation performance.
翻译:推荐人系统已成为现代网络应用程序的无处不在的一部分。 它们帮助用户发现新的相关项目。 今天的用户通过多年与这些系统的互动,已经对推荐人系统如何运作、目标是什么、用户如何操纵这些系统有了内在的理解。 我们把这个理解描述为建议人的理论。 在这项研究中,我们与40个推荐人系统用户进行了半结构性的访谈,以从经验上探索影响用户行为的有关因素。 我们基于对所收集数据的严格专题分析得出的调查结果表明,用户对推荐人系统的行为有着直观和精密的理解。 我们还发现,用户根据其理解、态度和意图改变了他们的互动,以唤起他们想要的推荐人行为。 最后,我们讨论了此类用户行为对推荐人行为的潜在影响。