To win the attention of the audience, presidential candidates rely on their own rhetorical methods. Hedges and boosters as metadiscourse markers have been the focus of many studies as the communicative strategies enabling speakers to soften the force of utterances or moderate their assertive force. TV news was used as the corpus of this study, whereas most of the previous studies have focused o...

In an election year, political messaging can become feisty or even violent. In the 2012 U.S. presidential election, Americans were inundated with statements that metaphorically referred to violence, such as “Romney slams Obama” and”Romney slaughtered Obama.” Such expressions grab our attention and resonate with our understanding of actual physical violence. Despite their frequent use in electio...

Drawing on network theory, this study considers the content of U.S. presidential debates and how candidates’ language differentiates them. Semantic network analyses of all U.S. presidential debates (1960–2004) were conducted. Results reveal that regardless of party affiliation, election winners were more central in their semantic networks than losers. Although the study does not argue causation...

One of the most used theories in the research of political debates is the functional theory of campaign discourse. However, the theory has been criticized for being too culturally limited. In the present article, a Finnish presidential debate is analyzed from the perspective of functional theory. The goal is to critically evaluate the applicability of functional theory to the analysis of Finnis...

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To evaluate how perceptions of presidential debates are structured by the media, we describe a three-wave field experiment in which subjects were incentivized to watch portions of a presidential debate and post-debate television coverage. We find that post-debate coverage has strong effects on candidate evaluations, with subjects’ perceptions moving in the direction of the ideological slant of ...

In this paper we tried to predict what a candidate in a political debate (namely George W. Bush) is going to say, based on what the moderator and the other candidate just said. In order to achieve that, we first used PCA to reduce the dimensionality of the problem, and then applied several regression models in order to do the actual predictions. While the PCA turned up some interesting patterns...