News from the future: A corpus linguistic analysis of future-oriented, unreal and counterfactual news discourse

Abstract

This article presents a corpus linguistic analysis of the development in future-oriented political journalism in four Danish newspapers in the period 1997-2013 (N = 2954 full articles = 1,553,038 word tokens). Keyword analysis and concordance analysis are applied within a framework of grammatical-semantic theory of tense and modal verbs and semantic-pragmatic theory of time meaning, modality and speech acts. The results suggest, unexpectedly, that the newspapers -and news reports in particular -seem to have become less future-oriented in the period. At the same time, however, the articles -and particularly news commentary, in itself increasing -might have become slightly more speculative. Thus, the journalists themselves have become the main source of 'guessing', that is, predicting and speculating, with the keywords vil (will) and ville (would), including unreal and counterfactual speculations in the past tenses.

Mediated Uncertainty

“…Over time journalists themselves have become more active in speculation and forecasting future events, rather than leaving this to their sources (Hansen 2015). When journalists speculate about the future, they introduce uncertainty in the news.…”

Data journalism’s many futures: Diagrammatic displays and prospective probabilities in data-driven news predictions

“…We determined whether the dominant temporal orientation of a piece was geared toward the future based on the headline and sub-headline. As indicators, we used grammatical markers of the future tense, that is, verbs, prepositions, temporal adjectives, or adverbs, but also considered the general temporal direction (references to developments or events still to happen), which must not necessarily be conveyed by a grammatical tense (Hansen, 2016; Simmerling and Janich, 2016). From the total number of available cases ( n = 2644), we selected only those with a recognizable projective outlook, which represented about 5.6% of the full sample ( n = 150).…”

Leveraging Machine Learning to Explain the Nature of Written Genres

“…She bases her study on corpus linguistics with the aim of showing the features used by these four authors that make this genre a very distinguished text in comparison to adult literature. We also need to include in this brief review the divergent approach on news by [11], where he also takes corpus linguistics as a basis in order to analyze futureoriented or unreal news using Danish articles with political themes that show a growing speculative intention. Finally, it seems clear that the rise of online linguistic genres offers us a wider spectrum of studies, with the paper published by [12] notable for its innovative approach to the much studied genre of reviews in the hotel domain, which emphasizes the communicative functions of each passage and also the linguistic structures that make them perfect examples of this genre.…”

“…We conducted our study to elucidate what are the most relevant features by considering a total of 16 alternative meth- ods 11 . First, Chi-square, mutual information and ANOVA were employed as filter methods.…”