No abstract

This article continues the line of research that combines the paradigm of Critical Discourse Analysis (CDA) with quantitative methods. We propose that Linguistic Inquiry and Word Count (LIWC), a software for automated text analysis widely used in social sciences, can enrich the CDA toolkit. The methodological advantage of LIWC is that its semantic categorization was developed and validated independently, which addresses the concerns about subjectivity. In two case studies we use LIWC to analyze the construction and representation of the 'Other' in mass media. Study 1 focuses on the representation of Russia in The New York Times (NYT) before and after its annexation of Crimea; Study 2 analyzes the change in sentiment toward Islam in NYT before and after 9/11. We find that in both cases the change in attitude is driven by an increase in negative emotion words rather than by a decrease in positive words.Keywords 9/11 and Islam, critical discourse analysis, mass media, positive and negative emotions, quantitative methods, representation of the 'Other', Russia's annexation of Crimea, sentiment analysis

Language is a powerful marker for social discrimination, often associated with stereotypes and prejudices against various social groups. However, less is known about the psychological role of language during ethnolinguistic conflicts. In such conflicts, the political rivalry is closely intertwined with language ideology. We consider two independent paths through which language might trigger social discrimination. The first one is related to linguistic identity, where a person could favor those who speak like her. The second one is related to political identity, where a person could favor those who use the language associated with the person's political views. In the context of the conflict in Ukraine, we find empirical support only for the political identity explanation and no support for the linguistic identity one.

Three studies test the link between word order in binomials and psychological and demographic characteristics of a speaker. While linguists have already suggested that psychological, cultural and societal factors are important in choosing word order in binomials, the vast majority of relevant research was focused on general factors and on broadly shared cultural conventions. In contrast, in this work we are interested in what word order can tell us about the particular speaker. More specifically, we test the degree to which word order is affected by factors such as gender, race, geographic location, religion, political orientation, and consumer preferences. Using a variety of methodologies and different data sources, we find converging evidence that word order is linked to a broad set of features associated with the speaker. We discuss the theoretical implications of these findings and the potential to use word order as a tool for analyzing large text corpora and data on the web.