Advances in natural language processing provide accessible approaches to analyze psychological open‐ended data. However, comprehensive instruments for text analysis of stereotype content are missing. We developed stereotype content dictionaries using a semi‐automated method based on WordNet and word embeddings. These stereotype content dictionaries covered over 80% of open‐ended stereotypes about salient American social groups, compared to 20% coverage from words extracted directly from the stereotype content literature. The dictionaries showed high levels of internal consistency and validity, predicting stereotype scale ratings and human judgments of online text. We developed the R package Semi‐Automated Dictionary Creation for Analyzing Text (SADCAT; https://github.com/gandalfnicolas/SADCAT) for access to the stereotype content dictionaries and the creation of novel dictionaries for constructs of interest. Potential applications of the dictionaries range from advancing person perception theories through laboratory studies and analysis of online data to identifying social biases in artificial intelligence, social media, and other ubiquitous text sources.

Rich people inhabit a distinct social category that may elicit universal images or perhaps different perceptions in different cultures. Whereas inequality research has mostly focused on lower socioeconomic classes, the current research investigates cultural variations of prejudices about rich groups, toward understanding societal dynamics. Three studies investigate stereotype content and evaluations of rich people in China and the United States, cultures that might be expected to differ. Consistent with U.S. data from the stereotype content model, Study 1 demonstrates mainland Chinese likewise view the rich in general ambivalently as competent but cold. Examining a more specific level, Study 2 identifies both distinctive and overlapping rich subgroups across the two cultures, but both reporting mixed stereotype content. Study 3 tests whether clearer cultural contrasts might occur in implicit (vs. explicit) stereotypes toward rich people: Both U.S. and Chinese respondents, however, expressed positive implicit stereotypes toward the rich compared with middle class, in contrast with their self-reported explicitly ambivalent (or, rarely, negative) wealth stereotypes. This research is the first to examine stereotype content about rich people on the subgroup level, and both implicit and explicit levels, offering theory-based social structure predictors of this culturally shared but somewhat variable stereotype content.

With globalization and immigration, societal contexts differ in sheer variety of resident social groups. Social diversity challenges individuals to think in new ways about new kinds of people and where their groups all stand, relative to each other. However, psychological science does not yet specify how human minds represent social diversity, in homogeneous or heterogenous contexts. Mental maps of the array of society’s groups should differ when individuals inhabit more and less diverse ecologies. Nonetheless, predictions disagree on how they should differ. Confirmation bias suggests more diversity means more stereotype dispersion: With increased exposure, perceivers’ mental maps might differentiate more among groups, so their stereotypes would spread out (disperse). In contrast, individuation suggests more diversity means less stereotype dispersion, as perceivers experience within-group variety and between-group overlap. Worldwide, nationwide, individual, and longitudinal datasets (n= 12,011) revealed a diversity paradox: More diversity consistently meant less stereotype dispersion. Both contextual and perceived ethnic diversity correlate with decreased stereotype dispersion. Countries and US states with higher levels of ethnic diversity (e.g., South Africa and Hawaii, versus South Korea and Vermont), online individuals who perceive more ethnic diversity, and students who moved to more ethnically diverse colleges mentally represent ethnic groups as more similar to each other, on warmth and competence stereotypes. Homogeneity shows more-differentiated stereotypes; ironically, those with the least exposure have the most-distinct stereotypes. Diversity means less-differentiated stereotypes, as in the melting pot metaphor. Diversity and reduced dispersion also correlate positively with subjective wellbeing.

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