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无需先验假设的D/s档案分类:聚类分析在社会数据中的应用

"Classifying D/s Profiles Without Prior Assumptions: An Application of Cluster Analysis to Social Data".

作者信息

La Corte Julie C

机构信息

Department of Mathematics, Computer Science & Engineering, Georgia State University, Atlanta, Georgia, USA.

出版信息

J Homosex. 2023 Jul 3;70(8):1549-1584. doi: 10.1080/00918369.2022.2036534. Epub 2022 Feb 15.

Abstract

Dominant/submissive role-play (D/s) is associated with specialized roles including Mistress, Master, Slave, Switch, Sadist, and Masochist. The current study uses cluster analysis to provide empirical evidence that no binary opposition or single spectrum constitutes a workable typology of individuals based on their affinities for these roles. The optimality of a particular choice of clustering scheme, including the number of clusters, is established using a replication technique which is presented in detail. A large number ( = 236,353) of individualized results (profiles) generated by the BDSM Test, a popular anonymous web survey, were analyzed. We hypothesize a two-dimensional typology of D/s profiles as the inferential result of our cluster analyses.

摘要

主导/服从角色扮演(D/s)与特定角色相关,包括女主人、男主人、奴隶、双性者、施虐者和受虐者。当前研究使用聚类分析来提供实证证据,表明不存在基于对这些角色的喜好的二元对立或单一谱系能够构成可行的个体类型学。使用详细介绍的复制技术确定了聚类方案特定选择的最优性,包括聚类数量。对一项流行的匿名网络调查“BDSM测试”产生的大量(=236,353)个性化结果(档案)进行了分析。作为聚类分析的推断结果,我们假设D/s档案的二维类型学。

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