The affiliative consequences of same-race and cross-race mimicry

Majka, Elizabeth A.; White, Michael; Bowling, La Vaun A.; García, Rosa Moreno; Skinner, Taylor L.; Bennett, Kyle F.; Bernstein, Michael J.; Sim, Jessica J.

doi:10.1080/00224545.2020.1719962

Cited by 2 publications

(1 citation statement)

References 37 publications

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“…One limitation of the current study is that it did not examine the influence of nationality, culture, gender, and age. Previous studies have consistently shown that individuals synchronize more with in-group members who share characteristics like nationality and gender while demonstrating less synchronization with out-group members 63 . Recent research has revealed differences in the degree of synchronization between in-group dyads (consisting of persons from the same nationality group) and inter-group dyads (consisting of individuals from other nationality groups) 55 , 56 , 64 .…”

Section: Discussionmentioning

confidence: 95%

Classifying interpersonal synchronization states using a data-driven approach: implications for social interaction understanding

Yozevitch,

Dahan,

Seada

et al. 2023

Sci Rep

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This study presents a data-driven approach to identifying interpersonal motor synchrony states by analyzing hand movements captured from a 3D depth camera. Utilizing a single frame from the experiment, an XGBoost machine learning model was employed to differentiate between spontaneous and intentional synchrony modes with nearly $$90\%$$ 90 % accuracy. Our findings demonstrate a consistent pattern across subjects, revealing that movement velocity tends to be slower in synchrony modes. These insights support the notion that the relationship between velocity and synchrony is influenced by the cognitive load required for the task, with slower movements leading to higher synchrony in tasks demanding higher cognitive load. This work not only contributes to the limited literature on algorithms for identifying interpersonal synchrony but also has potential implications for developing new metrics to assess real-time human social interactions, understanding social interaction, and diagnosing and developing treatment strategies for social deficits associated with conditions such as Autism Spectrum Disorder.

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