Applying machine learning to media analysis improves our understanding of forest conflicts

Abstract

Conflicts over the management and governance of forests seem to be increasing. Previous media studies in this area have largely focused on analysing the portrayal of specific conflicts. This study aims to review how a broad range of forest conflicts are portrayed in the Swedish media, analysing their temporal, spatial, and relational dimensions. We applied topic modelling, a machine learning approach, to analyse 53,600 articles published in the Swedish daily press between 2012 and 2022. We identified 916 topics, of which 94 were of interest for this study. Our results showed ten areas of forest conflicts: hunting and fishing (35 % of total coverage), energy (24 %), recreation and tourism (11 %), nature conservation (8 %), forest damages (6 %), international issues (5 %), forestry (5 %), reindeer husbandry (4 %), media and politics (2 %), and mining (1 %). The overall coverage of forest conflicts increased significantly over the study period, potentially reflecting an actual increase in forest conflicts. Some of the conflicts were continuously reported upon over time, while the coverage of others exhibited seasonal or event -related patterns. Four conflicts received most of their coverage in specific regions, while others were covered across the whole of Sweden. A relational analysis of the conflicts revealed three clusters of forest conflicts focused respectively on industrial, cultural, and conservation conflicts. Our results emphasise the value of using topic modelling to understand the overall patterns and trends of the media coverage of current land use conflicts, while also highlighting potential areas of emerging conflicts that may be of special interest for planners and policy -makers to monitor and manage.

Keywords

Forest policy; Agenda -setting power; Daily press; Topic modelling; BERTopic

Published in

Land Use Policy
2024, volume: 144, article number: 107254
Publisher: ELSEVIER SCI LTD

SLU Authors

• Hallberg-Sramek, Isabella

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    
  • Wageningen University

Associated SLU-program

SLU Future Forests

UKÄ Subject classification

Forest Science
Media Studies

Publication identifier

• DOI: https://doi.org/10.1016/j.landusepol.2024.107254

Permanent link to this page (URI)

https://res.slu.se/id/publ/131337