A large-scale, gamified online assessment of first impressions: The Who Knows project

被引:0
|
作者
Rau, Richard [1 ,2 ]
Grosz, Michael P. [1 ]
Back, Mitja D. [2 ,3 ,4 ]
机构
[1] HMU Hlth & Med Univ Potsdam, Inst Mind Brain & Behav, Potsdam, Germany
[2] Univ Munster, Munster, Germany
[3] Univ Munster, JICE Joint Inst Individualisat Changing Environm, Bielefeld, Germany
[4] Bielefeld Univ, Bielefeld, Germany
关键词
Interpersonal perception; Personality judgment; Accuracy; Gamification; Online assessment; PERSONALITY JUDGMENT; ACCURACY; AGREEMENT; TRAITS; SELF;
D O I
10.3758/s13428-025-02601-w
中图分类号
B841 [心理学研究方法];
学科分类号
040201 ;
摘要
Interpersonal judgments play a central role in human social interactions, influencing decisions ranging from friendships to presidential elections. Despite extensive research on the accuracy of these judgments, an overreliance on broad personality traits and subjective judgments as criteria for accuracy has hindered progress in this area. Further, most individuals involved in past studies (either as judges or targets) came from ad-hoc student samples which hampers generalizability. This paper introduces Who Knows (https://whoknows.uni-muenster.de), an innovative smartphone application designed to address these limitations. Who Knows was developed with the aim to create a comprehensive and reliable database for examining first impressions. It utilizes a gamified approach where users judge personality-related characteristics of strangers based on short video introductions. The project incorporates multifaceted criteria to evaluate judgments, going beyond traditional self-other agreement. Additionally, the app draws on a large pool of highly specific and heterogenous items and allows users to judge a diverse array of targets on their smartphones. The app's design prioritizes user engagement through a responsive interface, feedback mechanisms, and gamification elements, enhancing their motivation to provide judgments. The Who Knows project is ongoing and promises to shed new light on interpersonal perception by offering a vast dataset with diverse items and a large number of participants (as of fall 2024, N = 9,671 users). Researchers are encouraged to access this resource for a wide range of empirical inquiries and to contribute to the project by submitting items or software features to be included in future versions of the app.
引用
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页数:19
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