Climate Change Opinions in Online Debate Sites

Adrian Groza1, Pinar Ozturk2, Radu Razvan Slavescu1 and Anca Marginean1

  1. Technical University of Cluj-Napoca
    400128 Cluj-Napoca, Romania
  2. Norwegian University of Science and Technology
    Trondheim, Norway


Debate sites in social media provide a unified platform for citizens to discuss controversial questions and to put forward their ideas and arguments on the issues of common interest. Opinions of citizens may provide useful knowledge to stakeholders but manual analysis of arguments in debate sites is tedious, while computational support to this end has been rather scarce. We focus here on developing a technical instrumentation for making sense of a set of online arguments and aggregating them into usable results for policy making and climate science communication. Our objectives are: (i) to aggregate arguments posted for a certain debate topic, (ii) to consolidate opinions posted under several but related topics either in the same or different debate site, and (iii) to identify possible linguistic characteristics of the argumentative texts. For the first objective, we propose a voting method based on subjective logic [13]. For the second objective, we assess the semantic similarity between two debate topics based on textual entailment [28]. For the third objective, we employ various existing methods for lexical analysis such as frequency analysis or readability indexes. Although we focused here on the climate change, the method can be applied to any domain.

Key words

online debate analysis, aggregation of individual opinions, web text analysis, decision support for policy making

Digital Object Identifier (DOI)

Publication information

Volume 17, Issue 1 (January 2020)
Year of Publication: 2020
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

DownloadAvailable in PDF
Portable Document Format

How to cite

Groza, A., Ozturk, P., Slavescu, R. R., Marginean, A.: Climate Change Opinions in Online Debate Sites. Computer Science and Information Systems, Vol. 17, No. 1, 93-116. (2020),