Language abstraction in news about immigrants

Research by Dana Mastro and colleagues examined the use of abstraction in language describing immigrants in US newspapers. Variations in the use of abstraction in language and their consequences were first systematically described by the linguistic category model (Semin & Fiedler, 1988). The linguistic category model proposes that abstract language (i.e., adjectives) encourages people to infer that the described facts are more stable in time and across different contexts than when using concrete language (i.e., verbs). Subsequent research on abstraction in language describing different groups revealed that people talk about their ingroup (the group they belong to) and outgroups (the groups they don’t belong to) using different levels of language abstraction. They use abstract language when describing positive facts about their ingroup and when describing negative facts about outgroups. This tendency, coined linguistic intergroup bias, results in perceptions that positive characteristics about one’s ingroup and negative characteristics about outgroups are more stable and inherent to the given group; thus, reflecting more favorably on the ingroup than outgroups (Maass, Salvi, Arcuri, & Semin, 1989). Linguistic intergroup bias serves to maintain and enhance one’s own self-esteem based on belonging to favorably evaluated groups.

Mastro’s team (2014, 2017) performed a series of content analyses of newspaper coverage about Mexican immigration in the US and found exactly the tendency to describe undocumented immigrants in abstract and unfavorable language. Consistent with the linguistic intergroup bias, positive information about the ingroup and negative information about immigrants were worded using more abstract language than negative information about the ingroup and positive information about immigrants. Their experimental research (2014) showed that people who read abstract (vs. concrete) news about Mexican immigrants held more unfavorable attitudes toward Latinos. People who identified more with their nation (i.e., their belonging to the nation was important to them) showed stronger tendency to evaluate Latino immigrants negatively after reading abstract reports. Mastro’s et al. studies draw attention to subtle features of news that can polarize people’s attitudes toward immigrants. Their results underscore the need for more comprehensive analyses of the language used in the mass media.

 

Dragojevic, M., Sink, A., & Mastro, D. (2017). Evidence of Linguistic Intergroup Bias in US Print News Coverage of Immigration. Journal of Language and Social Psychology, 36, 462–472.

Maass, A., Salvi, D., Arcuri, L., & Semin, G. (1989). Language use in intergroup contexts: The linguistic intergroup bias. Journal of Personality and Social Psychology, 57, 981–993.

Mastro, D., Tukachinsky, R., Behm-Morawitz, E., & Blecha, E. (2014). News coverage of immigration:  The influence of exposure to linguistic bias in the news on consumer’s racial/ethnic cognitions. Communication Quarterly, 62, 135-154.

Semin, G., & Fiedler, K. (1988). The cognitive functions of linguistic categories in describing persons: Social functions and language. Journal of Personality and Social Psychology, 54, 558–568.