Disinformation, Propaganda & Soft Power Research Lab (DPS-Lab)

Disinformation and propaganda pose formidable global challenges that are threatening the sustainability of our collective future (WEF 2023). We take these threats seriously and are resolutely committed to addressing these problems through computational social science methods in close collaboration with computer science professionals., Our aim in this domain is the development of innovative methods for the detection and mitigation of news-related propaganda in various contexts, such as climate change, conflicts and health, that draw on solid theoretical development of the underpinning concepts of ideology and propaganda and their interrelations. Beyond academic outputs, we seek to extend the impact of this work into society through practice-oriented applications and social innovations.

Global politics is displaying a continuing trend towards a future of entrenched and reinforcing ideological rivalries. Within this context, we explore the field of ideological propaganda and its longer-term impacts/influence and systematically develop theoretical and conceptual approaches to enhance its study. Overall, our work contributes to empirical research by outlining how the diverse functions of ideology manifest in real-world contexts and shape the various techniques of propaganda within the communications domain.

The rapid evolution of generative AI models presents unprecedented challenges to news organisations, their stakeholders, governing bodies and audiences alike. This affects communications at local and global levels, ranging from social media platforms to AI-generated propaganda that can be created and distributed at exponentially increasing quantities and speeds. In our Lab, we seek to understand these changes by studying the technological, cultural and institutional conditions that shape the emergent digital communication environments, with a specific emphasis on the roles of global actors and the forms of ideologically driven communications, both globally and locally.

In today’s world, wars, crises and critical events are frequently characterised by the insertion of disinformation and propaganda in news. Given the current geopolitical environment, news and media organisations need to stay aware of – in both the shorter and longer terms – ideological propaganda and how it may disseminate into their news coverage. We tackle this issue by studying the changing media landscape of news production and the architectural dynamics that influence the evolution of media organisations in response to such challenges. Our projects in this domain will involve active cooperation with both international news organisations and local media organisations, as well as think tanks and startups.

Multiple BSc degrees Rutgers University | MSc LUT University

Research Interests: US-Russia space relations, strategic communications, propaganda, disinformation, Russia and the Soviet Union

Languages: English, Russian, Spanish, Finnish

Methodologies: Business Analytics, Sentiment Analysis, Large Language Models (LLMs)

Programming: R, SQL

Work experience: NASA, insurance companies

BSc and MSc Åbo Akademi, Finland

Research Interests: South Korean and North Korean relations, frozen conflicts, propaganda, disinformation, political communications and media of China and Japan, East Asian popular culture, democracy and democratization

Languages: Fluent in English, Swedish, Finnish, Japanese, Mandarin Chinese, Korean

Methodologies: Natural Language Processing (NLP), Machine Learning, Artificial Intelligence, Statistics

Programming: C, Python, R

Tools: MAXQDA

M.Soc.Sci University of Tampere, Finland | Charles University, Czech Republic | Sungkyunkwan University, Republic of Korea

Research Interests: cognitive warfare, intelligence studies, security studies,  arctic studies, strategic cultures, civilian and military crisis management, misinformation, propaganda, technoscientific futures and imaginaries, space politics, political history of Russia and the Soviet Union

Languages: Finnish, English, Swedish, French, German, Czech, Korean  

Methodologies: focus on qualitative and mixed method approaches. Experience in risk analysis and future scenarios. 

Programming: C#

Tools: ATLAS.ti

Work experience: Crisis Management Centre Finland, Finnish Defence Forces, UNICEF Finland

Doctoral Researcher at Finnish Center for Artificial Intelligence
M.A. International Christian University, Japan

Research Interests: AI Ethics, AI and Trust-building, East Asian popular culture, Music Industry, K-pop, Social Media

Languages:  fluent in English, Chinese, Japanese, Korean

Methodologies: qualitative and quantitative analysis with statistics and computational techniques, including SEM, Topic Modelling, and Sentiment Analysis.

Programming: Python 

Tools: SPSS, R, KH Coder 

Recent Publications:

• Yang, S. (2024). Trust in AI in China: A Mixed-Methods Approach to Understanding Public Opinion and Factors Affecting Trust Levels in AI. ICA Annual Conference 2024, Gold Coast, Australia.
• Yang, S., and Jung, J. (2023). Public Opinion Toward the Rape Victim in China: A Content Analysis of a MeToo Movement Case on Sina Weibo. ICA Annual Conference 2023, Toronto, Canada.

BSc Humboldt University, Germany | MSc Åbo Akademi, Finland

Research Interests: ecofeminism, propaganda, queer studies, sustainability, Singapore

Languages: German, English, Chinese, Burmese, French, Swahili, Japanese, Malay

Methodologies: quantitative research, statistics

Tools: SPSS, R

Work experience: multiple years of experience as a research assistant in the field of psychology, African history, and statistical evaluation

Recent publications:

• Bröder, C., Blüthmann, I., Grimm, A.-L., & Watermann, R. (2022). Ergebnisse der berlinweiten Befragung der Bachelor-Lehramtsstudierenden zum Übergang in den Lehramtsmaster. Freie Universität Berlin.
• Grimm, A. L. (2022). Trauma and Stigma: Myanmar Refugee Trauma, and German Attitudes Towards Refugees [Master’s Thesis]. Abo Akademi University.
• Kämpfe, B., Zimmermann, J., Dreisbusch, M., Grimm, A. L., Schumann, J. H., Naujoks, F., Keinath, A. & Krems, J. (2022). Preferences and Perceptions of Bidirectional Charging from a Customer’s Perspective – A Literature Review and Qualitative Approach. Proceedings, 177-191.

Doctoral Programme in Drug Research, University of Helsinki | MSc University of Helsinki, Finland

Research interests: crisis management, cross-sector collaboration, COVID-19, pharmaceutical supply chain, pharmaceutical industry, pharmacy, healthcare system development, Nordic countries

Language: Finnish, English, Swedish, German, Danish

Methodologies: quantitative and qualitative methods

Work experience: pharmaceutical industry (Novo Nordisk, ratiopharm), community pharmacies, hospital pharmacy (Helsinki University Hospital), Finnish Medicines Agency

Recent publications:

• Latonen, SH , Neuvonen, E. , Juppo, AM , Seeck, H. , & Airaksinen, M. (2024). Crisis management in community Pharmacies during a Pandemic. Research in Social and Administrative Pharmacy, 20(9), 940-948. https://doi.org/10.1016/j.sapharm.2024.06.010
• Latonen, S. H., Suominen, R. M., Juppo, A. M., Airaksinen, M., & Seeck, H. (2023). Organisation of cross-sector collaboration and its influence on crisis management effectiveness among pharmaceutical supply chain stakeholders during the COVID-19 pandemic. Public Health, 222, 196-204. https://doi.org/10.1016/j.puhe.2023.06.042
• Rimpelä, A.-K., Schmitt, M., Latonen, S., Hagström, M., Antopolsky, M., Manzanares, J. A., Kidron, H., & Urtti, A. (2016). Drug Distribution to Retinal Pigment Epithelium: Studies on Melanin Binding, Cellular Kinetics, and Single Photon Emission Computed Tomography/Computed Tomography Imaging. Molecular Pharmaceutics, 13(9), 2977-2986. https://doi.org/10.1021/acs.molpharmaceut.5b00787

MSc African Institute for Mathematical Sciences, Rwanda | LUT University, Finland

Research Interests: computer vision, Computational Social Science, climate-related startups, propaganda, social innovation, Africa

Languages: English, French, Kinyarwanda

Methodologies: quantitative and qualitative research, statistical analysis, actuarial science, machine learning, text analysis (NLP)

Programming: python (pandas, NumPy, scikit-learn, TensorFlow), R, Julia, SQL

Tools: Jupyter Notebook, VS Studio, PowerBI, Tableau

Work experience: World Bank, ILO (International Labor Organization), LadyAgri Impact Investment