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      An ingroup disadvantage in recognizing micro-expressions

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          Abstract

          Micro-expression is a fleeting facial expression of emotion that usually occurs in high-stake situations and reveals the true emotion that a person tries to conceal. Due to its unique nature, recognizing micro-expression has great applications for fields like law enforcement, medical treatment, and national security. However, the psychological mechanism of micro-expression recognition is still poorly understood. In the present research, we sought to expand upon previous research to investigate whether the group membership of the expresser influences the recognition process of micro-expressions. By conducting two behavioral studies, we found that contrary to the widespread ingroup advantage found in macro-expression recognition, there was a robust ingroup disadvantage in micro-expression recognition instead. Specifically, in Study 1A and 1B, we found that participants were more accurate at recognizing the intense and subtle micro-expressions of their racial outgroups than those micro-expressions of their racial ingroups, and neither the training experience nor the duration of micro-expressions moderated this ingroup disadvantage. In Study 2A and 2B, we further found that mere social categorization alone was sufficient to elicit the ingroup disadvantage for the recognition of intense and subtle micro-expressions, and such an effect was also unaffected by the duration of micro-expressions. These results suggest that individuals spontaneously employ the social category information of others to recognize micro-expressions, and the ingroup disadvantage in micro-expression stems partly from motivated differential processing of ingroup micro-expressions.

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          G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.
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              Intergroup bias.

              This chapter reviews the extensive literature on bias in favor of in-groups at the expense of out-groups. We focus on five issues and identify areas for future research: (a) measurement and conceptual issues (especially in-group favoritism vs. out-group derogation, and explicit vs. implicit measures of bias); (b) modern theories of bias highlighting motivational explanations (social identity, optimal distinctiveness, uncertainty reduction, social dominance, terror management); (c) key moderators of bias, especially those that exacerbate bias (identification, group size, status and power, threat, positive-negative asymmetry, personality and individual differences); (d) reduction of bias (individual vs. intergroup approaches, especially models of social categorization); and (e) the link between intergroup bias and more corrosive forms of social hostility.
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                Author and article information

                Contributors
                Journal
                Front Psychol
                Front Psychol
                Front. Psychol.
                Frontiers in Psychology
                Frontiers Media S.A.
                1664-1078
                25 November 2022
                2022
                : 13
                : 1050068
                Affiliations
                [1] 1Department of Psychology, School of Educational Science, Hunan Normal University , Changsha, China
                [2] 2Cognition and Human Behavior Key Laboratory of Hunan Province, Hunan Normal University , Changsha, China
                Author notes

                Edited by: Wenfeng Chen, Renmin University of China, China

                Reviewed by: Chao Liu, Beijing Normal University, China; Luyan Ji, Guangzhou University, China

                *Correspondence: Qi Wu, sandwich624@ 123456yeah.net

                These authors have contributed equally to this work

                This article was submitted to Emotion Science, a section of the journal Frontiers in Psychology

                Article
                10.3389/fpsyg.2022.1050068
                9732534
                36507018
                cf521053-d696-4cd0-b26b-989232663087
                Copyright © 2022 Wu, Peng, Xie, Lai, Liu and Zhao.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 21 September 2022
                : 08 November 2022
                Page count
                Figures: 6, Tables: 2, Equations: 0, References: 75, Pages: 14, Words: 10447
                Funding
                Funded by: Outstanding Young Scientific Research Project of Hunan Provincial Department of Education
                Award ID: 19B361
                Categories
                Psychology
                Original Research

                Clinical Psychology & Psychiatry
                micro-expression,macro-expression,recognition,emotion perception,intergroup bias,ingroup advantage,ingroup disadvantage

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