Probing the discourses of climate change (CC)
What can automatic text mining reveal about CC communication?
In a series of interrelated student projects, spanning across several seminars and research modules since 2020, we apply text mining methods to a variety of text corpora (some of which we built ourselves). The overarching goal is to identify patterns, opinions and arguments brought forward in different CC discourses.
A video that introduces five of our recent student projects (largely in German), targeting the general public, is available at the online "Potsdamer Tag der Wissenschaften" 2021 here.
Corpora
- GerCCT: 12.000 pairs of German Climate Change Tweets, collected at DRL (see Schäfer/Stede 2020 below)
- NatSciCC: 490 editorials from Nature and Science (1966-2015), manually annotated by Hulme et al. 2018 for thematic framing categories. We built a digital version of the corpus.
- NYTAC: New York Times Annotated Corpus. We identified 10.000 articles related to CC.
- CMV-CC: A CC subset of the "Change My View" subreddit corpus compiled by Webis.
Glossary
- Glossary: We built a linguistically-oriented online glossary of 250 German climate compound nouns used in politically-oriented discourse
Activities
- Framing in NatSciCC: Following up on the work of Hulme et al. 2018, we analyze the linguistics of framing in editorials.
- Classifying the NatSciCC texts: Focusing on the problem of imbalanced data, we aim at automatically reconstructing the topic frame annotations by Hulme et al. 2018 (see Bracke 2020 below).
- Tracking CC in NYTAC: We use unsupervised methods to detect patterns in CC reporting in The New York Times (1987-2007).
- Argumentation in Twitter exchanges: We study various subtaks of argumentation mining on the GerCCT corpus.
- News headlines: We searched the archives of German newspapers for climate change articles, collected their headlines and study trends of term usage
People
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BSc students 2022 (Computational Linguistics): Noël Simmel
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MSc students 2022 (Cognitive Systems): Raunak Agarwal, Luka Borec, Anna Goecke, Juliane Hanel, Neele Charlotte Kinkel, Nailia Mirzakhmedova
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PhD student: Robin Schäfer
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Inter/national collaborators: Nic Badullovich (ANU Climate Change Institute, Canberra), Ronny Patz (Hertie School, Berlin), Patrick Saint-Dizier (Univ. Paul Sabatier, Toulouse), Maria Skeppstedt (Inst. for Language and Folklore, Sweden)
Contact
- Manfred Stede (stede@uni-potsdam.de)
Related publications:
- Francesca Grasso, Ronny Patz, and Manfred Stede. NYTAC-CC: A Climate Change Subcorpus based on New York Times Articles. In Proceedings of CLiC-it - 10th Italian Conference on Computational Linguistics. Pisa, Italy, 2024. (to appear). [Bibtex]
- M. Stede, A. Goecke, N. Simmel, and B. Schneider. Der reine Klimawahnsinn! Zur Konzeption eines Diskursglossars von Klimakomposita. In M. Beißwenger, E. Gredel, L. Lemnitzer, and R. Schneider, editors, Korpusgestütze Sprachanalyse - Grundlagen, Anwendungen und Analysen. Narr, Tübingen, 2023. [Bibtex]
- Manfred Stede, Yannic Bracke, Luka Borec, Neele Charlotte Kinkel, and Maria Skeppstedt. Framing Climate Change in Nature and Science Editorials: Applications of Supervised and Unsupervised Text Categorization. Computational Social Science, 2023. [Bibtex] [DOI]
- Robin Schaefer, Christoph M. Abels, Stephan Lewandowsky, and Manfred Stede. Communicating Climate Change: A Comparison Between Tweets and Speeches by German Members of Parliament. In Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis. Toronto, Canada and Online, July 2023. Association for Computational Linguistics. [Bibtex] [PDF]
- Juliane Hanel. Transformer-Based Analysis of Climate Discourse and Green Party Evolution in German Party Manifestos. Unpublished M.Sc. Thesis, 2023. [Bibtex] [PDF]
- Robin Schaefer and Manfred Stede. GerCCT: An Annotated Corpus for Mining Arguments in German Tweets on Climate Change. In Proceedings of the 13th Language Resources and Evaluation Conference (LREC). Marseille, France, 2022. European Language Resources Association. [Bibtex] [PDF]
- Noël Simmel. Klimaretter oder Klimaspinner? Entwicklung einer Web-App zum Klimawandeldiskurs. Unpublished B.Sc. Thesis, 2022. [Bibtex] [PDF]
- M. Stede and R. Patz. The climate change debate and natural language processing. In Proc. of the 1st Workshop on NLP for positive impact (ACL). Online, 2021. [Bibtex] [PDF]
- Yannic Bracke. Automatic text classification with imbalanced data: Building a frame classifier from a corpus of editorials. Unpublished B.Sc. Thesis, 2020. [Bibtex]
- Robin Schäfer and Manfred Stede. Annotation and detection of arguments in tweets. In Proceedings of the 7th Workshop on Argument Mining, 53–58. Online, December 2020. Association for Computational Linguistics. [Bibtex] [PDF]