In everyday life, people use language to communicate evaluative messages about social categories. A selection bias in language across two social dimensions not previously integrated was examined: a self-inclusive/self-exclusive dimension and an individual/collective dimension. Pronouns as markers for social categories were adopted (I, We, He/She, and They), and a new measure was developed (the Evaluative Sentence Generating task) to investigate the evaluative context selected for the pronouns. Results demonstrate that individuals select a more positive context for self-inclusive than self-exclusive pronouns and a more positive context for individual than collective pronouns. However, in an interpersonal context, evaluative differences between I and We diminished, whereas in an intergroup condition the evaluative gap between self-inclusive and self-exclusive pronouns was magnified.

This paper examines whether pronouns in news media occurred in evaluative contexts reflecting psychological biases. Contexts of pronouns were measured by computerized semantic analysis. Results showed that self-inclusive personal pronouns (We, I) occurred in more positive contexts than self-exclusive pronouns (He/She, They), reflecting self- and group-serving biases. Contexts of collective versus individual pronouns varied; We occurred in more positive contexts than I, and He/She in more positive contexts than They. The enhancement of collective relative to individual self-inclusive pronouns may reflect that media news is a public rather than private domain. The reversed pattern among self-exclusive pronouns corroborates suggestions that outgroup derogation is most pronounced at the category level. Implications for research on language and social psychology are discussed.

Previous research has shown a male bias in the media. This study tests this statement by examining how the pronouns She and He are used in a news media context. More specifically, the study tests whether He occurs more often and in more positive semantic contexts than She, as well as whether She is associated with more stereotypically and essential labels than He is. Latent semantic analysis (LSA) was applied to 400 000 Reuters' news messages, written in English, published in 1996-1997. LSA is a completely data-driven method, extracting statistics of words from how they are used throughout a corpus. As such, no human coders are involved in the assessment of how pronouns occur in their contexts. The results showed that He pronouns were about 9 times more frequent than She pronouns. In addition, the semantic contexts of He were more positive than the contexts of She. Moreover, words associated with She-contexts included more words denoting gender, and were more homogeneous than the words associated with He-contexts. Altogether, these results indicate that men are represented as the norm in these media. Since these news messages are distributed on a daily basis all over the world, in printed newspapers, and on the internet, it seems likely that this presentation maintains, and reinforces prevalent gender stereotypes, hence contributing to gender inequities.