title: Linguistic intergroup bias in political communication.
abstract: The Linguistic Intergroup Bias (LIB) illustrates the disposition to communicate positive in-group and negative out-group behaviors more abstractly than negative in-group and positive out-group behaviors. The present research examined the function of language in reinforcing this bias in political communication. To illustrate the LIB, the Linguistic Category Model (LCM) was used, including a nouns category. Because social stereotypes are usually conveyed by nominal terms, the aim was to observe the relationship between stereotypes and language in political communication. Moreover, we were interested in analyzing the psychological processes that drive the LIB. Therefore, we verified whether the LIB is more related to language abstractness than to agent-patient causality. Several political debates and interviews, which took place before the latest Italian provincial elections, were analyzed. Results suggested that the language politicians use in communicating about political groups are conceptualized as stereotypes rather than as trait-based categories. Moreover, it seems that the LIB could not be explained only at a lexical level. Social implications of the present findings in interpersonal relations and causal attribution were discussed.
authors.affiliation: Faculty of Science Education, University of Milan-Bicocca, piazza dell'Ateneo Nuovo 1, U6 4th Floor 20126 Milan, Italy. luigi.anolli@unimib.it
authors.forename: Luigi
authors.initials: L
authors.lastname: Anolli
authors.forename: Valentino
authors.initials: V
authors.lastname: Zurloni
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Riva
mesh_terms: D000328:Adult; D003142:Communication; D001330:Electronic Data Processing; D005260:Female; D006801:Humans; D008297:Male; D010565:Persuasive Communication; D011057:Politics; D011578:Psycholinguistics; D012660:Semantics; D012919:Social Behavior; D012933:Social Identification; D012984:Software; D013240:Stereotyping; D014705:Verbal Behavior