Comprehensive stereotype content dictionaries using a semi‐automated method

By Gandalf Nicolas, Xuechunzi Bai, Susan T. Fiske. European Journal of Social Psychology, 2020

103 citations recorded by the source corpus.

wileyonlinelibrary.com/journal/ejsp Eur J Soc Psychol. 2021;51:178–196. © 2020 John Wiley & Sons, Ltd. Text data are everywhere. Researchers may obtain text data from sources such as the internet, literary collections, archival entries, and experimental psychology's open-ended responses. Compared to traditional response scales in psychological research, embracing text data allows more unobtrusive and unconstrained approaches to measurement. For example, social media data provide information about participants’ cognitions, free from demand characteristics associated with some laboratory studies (see Meshi et al., 2015). Using open-ended (vs. forced-choice) responses in controlled settings also enables more ecologically valid and data-driven study of psychological processes and content. These benefits appear in studying emotion (Gendron et al., 2015) and racial categorization (Nicolas et al., 2018), challenging previously held findings by employing free-response measures that circumvent researcher constraints on participants’ responses. For example, despite several studies showing that Americans categorize Black-White mixed-race faces as Black when only allowed to make Black versus White categorizations (see Nicolas & Skinner, 2017), in a free response task participants most frequently indicated perceiving these targets to be Hispanic or Middle-Eastern (Nicolas et al., 2018). These kinds of online and open-ended text data, however, often need some form of dimensionality reduction and numerical representation for interpretation (e.g., due to the large number of words that may refer to the same overarching construct of interest), making text analysis methods necessary. Language and text analysis have a long history in psychology (e.g., Dewey, 1910; Miller, 1951; see Boyd, 2017 for a review) and affiliated fields ranging from Sociology and Political Science (see Lucas et al., 2015) to Computer Science (see Nerbonne, 2003). In social and personality psychology in particular, numerous studies have made use of text analysis to obtain novel insights into human traits and behaviors. For example, studies into status differences in language use have shown that higher (vs. lower) status individuals tend to use we more often than I as pronouns (e.g., Kacewicz et al., 2014). Received: 12 March 2020 | Accepted: 29 September 2020 DOI: 10.1002/ejsp.2724

Subfields: General Social Sciences, Sociology and Political Science

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