Abstract
Structural linguistic features are often overlooked yet potentially important aspects of journalistic practice. Especially in news reporting on climate change, these features can play a crucial role as the proper use of language is tied to message credibility, processing fluency and knowledge retention, which can positively influence the reader to take more climate action. This article analyzes language use in Danish news articles on climate change using a sample of around 32,000 articles from four different outlet types (quality news, niche papers, tabloids, and public service broadcasters) published from 1990 to 2021. We create a machine-learning model of text complexity covering this concept's semantic and syntactic dimensions. Our findings confirm expected differences in complexity between news outlets, highlighting tabloid articles as engaging with higher semantic complexity, while quality papers and niche papers exhibit higher syntactic complexity. We observe a significant decrease in semantic complexity and a slight increase in syntactic complexity over time, a trend towards more generic language, and an increased use of pronouns, verbs, and adverbs. Most of these changes can be attributed to the emergence of articles by public service broadcasters. Articles by public service broadcasters are characterised by high syntactic complexity, which we consider problematic due to their popularity among the general public.
| Originalsprog | Engelsk |
|---|---|
| Titel | Proceedings of DHNB 2024 Digital Humanities in the Nordic and Baltic Countries 8th Conference |
| Status | E-pub ahead of print - 30 maj 2024 |