Environmental Discourses and the Spread of Multilingual (Dis)information in Social Networks

Application period: 11 June – 10 August, 2026

Research project description

User‑generated content on social media offers an exceptionally large and diverse source of empirical data for examining environmental discourse in multilingual contexts. Social media data make it possible not only to investigate how people use linguistic and discursive resources to discuss environmental phenomena and climate‑smart solutions, but, when combined with metadata on time, location, and interaction patterns, also to observe how messages spread, how they relate to one another, and which communities engage with them. Together, these data enable detailed analyses of the circulation of discourses, information, and disinformation within social networks.

This project seeks a doctoral candidate interested in how environment‑related discourses circulate within digital social networks. The main objective of the doctoral project is to investigate how discourses and (dis)information about climate, the environment, and climate‑smart solutions spread in digital social media networks. The work will also incorporate multilingual perspectives, including tracing how concepts travel across linguistic communities and linguistic borders. The specific concepts and analytical focus will be defined during the planning phase, but they should align with the core themes of the doctoral school.

The selected candidate will work with large‑scale datasets consisting of user‑generated social media content enriched with metadata. These data are time stamped and include social network information,w enabling the candidate to trace how concepts emerge, evolve, and circulate across communities over time. Altogether, the datasets comprise approximately 40 billion words produced by hundreds of thousands of accounts worldwide.

Academic background and skills of the applicant

An ideal candidate holds a master’s degree in linguistics (general or any of its subfields), in computational linguistics, translation studies, or a closely related field relevant to the study of language. They should be comfortable working with large‑scale datasets using computational tools such as R or Python, while also possessing strong expertise in the nuances of language use. Excellent written and oral communication skills in English are essential for the position, and the selected candidate must fulfill the language skills requirements of the Doctoral Programme of the Philosophical Faculty at UEF (see https://www.uef.fi/en/degree-programme/doctoral-programme-of-the-philosophical-faculty (Admission criteria)). The ability to conduct linguistic analysis in more than one language is considered an advantage. The project provides access to digital infrastructure and technical support; prior experience with high‑performance computing is an advantage but not required.

Doctoral programme and research group

Doctoral education in the University of Eastern Finland is arranged in seven discipline specific or thematic doctoral programmes. This research project will be located in the Doctoral Programme of the Philosophical Faculty, and the submitting department is the School of Humanities.

Depending on the orientation, the student finds peer group from the projects by the supervisors. These include three Research Council of Finland-funded projects: COMET (Weak-tie Hypothesis in Complex Digital Networks) and FIN-CLARIAH (the Common Language Resources and Technology Infrastructure), a state-of-the-art lighthouse infrastructure funded by the Research Council, as well as the DECA (Democratic Epistemic Capacities in the Age of Algorithms) project consortium funded by the Strategic Research Council established within the Research Council of Finland.

Partners / Secondments

University of Porto, Centre for Linguistics (CLUP), hosted by Assistant Professor Rui Sousa-Silva.

University of Birmingham, Department of Linguistics and Communication, hosted by Prof. Jack Grieve

Other interdisciplinary, international and/or intersectoral collaboration

This project involves potential collaboration with Language Technology & Data Analysis Laboratory, University of Queensland, Dr. Martin Schweinberger (https://ladal.edu.au/) and the national DECA project consortium (https://www.decatutkimus.fi/home) formed by researchers from the fields of media, communications and journalism research, social psychology, sociology, law, translation studies and IT.

Intersectoral and interdisciplinary collaboration is strengthened through DP-FOBI’s three summer schools involving academic supervisors, non-academic partners, and other stakeholders, enabling hands-on interaction and knowledge exchange.

Supervisors and related research

Mikko Laitinen

Mikko Laitinen is a Professor of English at the University of Eastern Finland and an elected member of the Finnish Academy of Sciences and Letters. His research focuses on language change in digital social networks, and he is the PI of “Weak-tie Hypothesis in Complex Digital Networks” (COMET), which is funded by the Research Council of Finland for 2024–28, and one of the leaders in the national research infrastructure for digital humanities (FIN-CLARIAH). He has published over 70 peer-reviewed articles, is the co-editor of Data-intensive Investigations into English (CUP, 2025), and together with a colleague from the University of Queensland acts as chief editor of a book series Language, Data Science and Digital Humanities (Bloomsbury Academic).

Laitinen has six ongoing doctoral projects; 3 doctoral dissertations completed, over 150 MA theses supervised since 2012 in two orientations (English language and culture, Linguistic Data Sciences)

Maarit Koponen

Maarit Koponen is Professor of Translation Studies at the University of Eastern Finland. She leads the research group Translation and multilingual communication in digital society (TraDiSoc) and is the principal investigator for the UEF sub-project Linguistic barriers, algorithms and epistemic capabilities of the research consortium Democratic epistemic capacities in the age of algorithms (DECA, 2022-2028), funded by the Strategic Research Council. Her research focuses on theoretical and practical aspects of translation technology, particularly the use of machine translation and generative AI. Koponen’s current research projects investigate the use of automatic translation and generative AI for disseminating and accessing information with a focus on cross- and multilingual communication related to public services and societal information.

Koponen has 4 ongoing doctoral dissertations; 3 post-doctoral researchers supervised as PI of the DECA sub-project; Master’s degree supervision (Master’s Degree Programme on Linguistic Data Sciences, since 2021): 15 completed, 6 ongoing.

Laitinen, Mikko, Paula Rautionaho & Irene Taipale. 2026. Data-Intensive Approaches to English Linguistics. In M. Laitinen & P. Rautionaho (eds.), Data-intensive Investigations into English. (Studies in English Language), 1–19. Cambridge: Cambridge University Press. doi: 10.1017/9781009415682.

Laitinen, Mikko & Paula Rautionaho. 2025. Reuse of social media data in corpus linguistics. International Journal of Corpus Linguistics. doi: 10.1075/ijcl.24136.lai

Laitinen, Mikko & Masoud Fatemi. 2024. Testing the weak-tie hypothesis with social media. In Céline Poudat & Mathilde Guernut (eds.), Proceedings of the 11th Conference on CMC and Social Media Corpora for the Humanities. 11th Conference on CMC and Social Media Corpora for the Humanities (CMC 2024), CORLI; Université Côte d’Azur, 2024, 46-51. doi: ffhalshs-04673776v1.

Koponen, M., & Nurminen, M. (2024). Risk management for content delivery via raw machine translation. In M. Winters, S. Deane-Cox, & U. Böser (Eds.), Translation, Interpreting and Technological Change: Innovations in Research, Practice and Training (pp. 111–135). Bloomsbury.

Koponen, M., Sousa-Silva, R., & Pareja-Lora, A. (2026). Language Rights in the Metaverse: The Implications of Translingual Metaverse Communication. In R. Neuvonen & J. Viljanen (Eds.), Real Rights in Virtual Worlds (p. in press). Edward Elgar Publishing.

Nurminen, M., & Koponen, M. (2020). Machine translation and fair access to information. Translation Spaces, 9(1), 150–169. https://doi.org/10.1075/ts.00025.nur