Critical reflections on user studies’ evaluation methods for group recommender systems

IF 6 2区 计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS
Francesco Barile, Pierre Hurlin, Cedric Waterschoot, Nava Tintarev
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引用次数: 0

Abstract

Social choice-based aggregation strategies are often used in group recommender systems to aggregate individual preferences or recommendations. However, previous works evaluating group recommenders with user studies found that the diversity of the group members’ preferences impacts the effectiveness of the strategies.
In this paper, we highlight and address the methodological limitations of those previous works. Specifically, the methodologies we introduce demonstrate the following three novelties: 1) We evaluated the strategies from the viewpoint of an “internal evaluator”; 2) We introduced a novel methodology for modeling a fictional but realistic group with specific preference profiles for the group members, defining scenarios with concrete users and items, that are still mapped to specific group configurations; 3) We evaluated the understanding of the participants, by measuring how well they can successfully apply the aggregation strategy to a new scenario.
To do this we performed a randomized controlled trial (n=444) using a mixed design with two between-subject factors (the used aggregation strategy and the presented explanation type), and a within-subject factor (the group configuration). Our results, with friend groups, showed significant differences in the effectiveness of the aggregation strategies depending on the specific group configuration (i.e., depending on the internal diversity of group members’ preferences), with noticeable differences between evaluations of what is good for the group – external evaluation – and what is good for the participant – internal evaluation. We conclude with methodological implications for group recommender systems.
对群组推荐系统中用户研究评价方法的批判性思考
基于社会选择的聚合策略通常用于群体推荐系统中,以聚合个人偏好或推荐。然而,先前用用户研究评估群体推荐的研究发现,群体成员偏好的多样性会影响策略的有效性。在本文中,我们强调并解决了这些先前工作的方法局限性。具体而言,我们介绍的方法展示了以下三个新颖之处:1)我们从“内部评估者”的角度评估战略;2)我们引入了一种新的方法来建模一个虚构但现实的群体,并为群体成员提供特定的偏好配置文件,定义具有具体用户和项目的场景,这些场景仍然映射到特定的群体配置;3)我们通过衡量参与者如何成功地将聚合策略应用于新场景来评估参与者的理解程度。为此,我们进行了一项随机对照试验(n=444),采用混合设计,其中包含两个受试者之间因素(使用的聚合策略和提出的解释类型)和一个受试者内部因素(组配置)。在朋友组中,我们的结果显示,根据特定的群体配置(即,取决于群体成员偏好的内部多样性),聚合策略的有效性存在显著差异,在对群体有利的评估(外部评估)和对参与者有利的评估(内部评估)之间存在显著差异。我们总结了小组推荐系统的方法含义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Human-Computer Studies
International Journal of Human-Computer Studies 工程技术-计算机:控制论
CiteScore
11.50
自引率
5.60%
发文量
108
审稿时长
3 months
期刊介绍: The International Journal of Human-Computer Studies publishes original research over the whole spectrum of work relevant to the theory and practice of innovative interactive systems. The journal is inherently interdisciplinary, covering research in computing, artificial intelligence, psychology, linguistics, communication, design, engineering, and social organization, which is relevant to the design, analysis, evaluation and application of innovative interactive systems. Papers at the boundaries of these disciplines are especially welcome, as it is our view that interdisciplinary approaches are needed for producing theoretical insights in this complex area and for effective deployment of innovative technologies in concrete user communities. Research areas relevant to the journal include, but are not limited to: • Innovative interaction techniques • Multimodal interaction • Speech interaction • Graphic interaction • Natural language interaction • Interaction in mobile and embedded systems • Interface design and evaluation methodologies • Design and evaluation of innovative interactive systems • User interface prototyping and management systems • Ubiquitous computing • Wearable computers • Pervasive computing • Affective computing • Empirical studies of user behaviour • Empirical studies of programming and software engineering • Computer supported cooperative work • Computer mediated communication • Virtual reality • Mixed and augmented Reality • Intelligent user interfaces • Presence ...
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