Linguistic Devices used in Newspaper Headlines

Abstract

Nowadays mass media plays crucial roles in people’s lives. Online newspapers constitute a part of media discourse, which makes for extremely important bodies of text for the purposes of research in discourse analysis. In news headlines, careful and sensitive use is made of linguistic devices in order to make the headlines unique and different, influence the readers, create trust for the newspaper, and, most importantly, invite and encourage the reader to proceed to the whole story and the main body of the report/news report. In this spirit, this study is a linguistic analysis of headlines in the political section of established online American newspapers. The data for this study comprises 50 headlines collected from 5 online newspapers revolving around the theme of Donald Trump. It aims to explore the linguistics structure of newspaper headlines in the sample articles from these 5 most widely read newspapers: The Wall Street Journal, The New York Times, USA Today, Los Angeles Times, and Washington Post. Most studies on headlines have been undertaken using Critical Discourse Analysis perspectives, but in this qualitative-quantitative study, use is made of the model by Montgomery (2007) that takes account of a more comprehensive picture that pays due respects to linguistic, semantic and discursive properties of headlines alongside each other in a complete package. The findings are mapped out in the form of figures and charts. The results of the frequency analysis showed that newspapers mostly used ‘full sentence’ and ‘ellipsis’ in their headlines. The qualitative analysis revealed that most of the semantic, linguistic and discursive strategies used in headlines are geared to the ‘tactical incompleteness strategy’, a helpful notion and a part of Montgomery’s model. We suggest here that it is manifest in more pervasive ways than Montogomery gives us to understand in his explication of the model. There are implications to this study for teaching the reading skill, and for discourse analysis