Research
My research bridges human–computer interaction, computational social science, media studies, and political science, with a focus on the digital dimensions of society. My current interests include:
Ideologies and technology
Core challenge: How do political ideologies manifest themselves through digital artifacts, including social media services and public sector IT?
It is well known through science and technology studies that artifacts have politics. Contemporary researchers provide a vast pool of examples where these politics have harmed or oppressed someone. However, we lack understanding how an artifact gains its politics and how it relates to the real-world politics. To fill this gap, I have worked to detail how different ideologies prefer or dislike particular design approaches to try to examine how such approaches then may push for actions and behaviour aligned with said ideologies.
Publications in this area include
- Epp, F. A., Haapoja, J., & Nelimarkka, M. (2025). Affordances and Design Principles of The Political Left and Right. Proceedings of the ACM on Human-Computer Interaction, 9(7), 1–24.
- Grön, K., & Nelimarkka, M. (2020). Party Politics, Values and the Design of Social Media Services. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW2), 1–29.
Rebiased language models
Core challenge: Can we use language models to conduct social analysis from a specific conceptual and theoretical perspective?
Extensive body of work has shown that language models are biased: for example they appear to have political leanings. (While the jury is still out what leaning it might be; results are mixed.) At the same time, many social scientists are using LLMs to "measure" content, produce synthetic data etc. Is there a way to rethink the role of bias and instead of seeing it as an asset, a perspective to consider of?
Work in this area include
From text to visual and multi-modal data
How can we as social scientists make meaningful use of computational methods with visual and multi-modal data?
Increasingly, media is visual, auditory or mix of these. Social scientists have just started to grasp how to use computational methods meaningfully with text data, but this calls for transformation. How should we approach images and are there ways we could learn from our past mishaps with the textual data?
Publications in this area include
- Hokka, J., & Nelimarkka, M. (2020). Affective economy of national-populist images: Investigating national and transnational online networks through visual big data. New Media & Society, 22(5), 770–792.
- Berg, A., & Nelimarkka, M. (2023). Do you see what I see? Measuring the semantic differences in image‐recognition services’ outputs. Journal of the Association for Information Science and Technology.
- COSLAB GUI
Interested in these?
If you are a master student, please contact me or visit my office hours.
If you are thinking about doing a PhD, please see further details about doing a PhD.
If you are a researcher interested to hear more, please contact me or visit my office hours.