How Clickbait is Used in Russian and American Media

In this research we present the mechanics of creating clickbait headlines (also known as misleading headlines) in Russian and American Internet media. We also define the conditions that should be met for clickbait headlines to be more efficient in drawing readers' attention to an article, compared to "honest" headlines. For the purpose of this study we created a Corpus of News Headlines (CNH), which contains over 1700 honest and clickbait headlines from 20 Russian and American media. This paper features both a theoretical description of the corpus and a code for a web-site which researchers will be able to access the corpus through. Having analyzed the data from corpus, we created a detailed classification of linguistic strategies that journalists use to compose misleading headlines as well as successfully conducted a linguacultural comparison of Russian and American media and the news headlines published in these countries. Moreover, in the current thesis we performed an experiment with 2000 participants and a big empirical study which revealed the conditions (characteristics of a piece of news narrated, special features of a medium, its target audience, etc.), under which clickbait headlines are more efficient than honest ones. Furthermore, in this thesis we developed a unique framework which allows for detailed meta-linguistic description of a medium and for predicting the percentage of clickbait headlines on a news agencies' web-site with meta-linguistic characteristics given.