The Methodological Unit organizes a weekly Brown Bag Seminar to highlight novel methodological approaches in humanities and social sciences. The idea of the meetings is to introduce methodological innovations and cutting-edge research in various disciplines in an easily accessible manner and have an interdisciplinary discussion in an easy-going atmosphere over lunch. Bring your own lunch, we bring fresh methodological topics!
Every Wednesday at 12.00.
The next seminar session is held at Fabianinkatu 24a, 5th floor, room 532.
You are welcome to join us in person, or online via Zoom.
There will be a 20-minute introduction to the methodological theme, followed by an open discussion of 40 minutes. The seminars are open to everybody. We expect a multidisciplinary and methodologically curious audience from different faculties and units of the central campus. The language of the meetings can be Finnish or English.
The most important prerequisite for participation is not methodological expertise, but an open mind towards new methodological innovations and discussion across methodological and disciplinary boundaries.
Scroll down for the upcoming program of Brown Bag Seminars. To get notified on updates sign up for our mailing list or follow us on social media.
Digital research materials increasingly combine multiple forms of evidence: moving and still images, speech, sound, written language, webpages, metadata and pre-existing structured datasets. Yet computational research methods frequently analyse these materials separately or reduce them to whichever modality is easiest to process. Text may be detached from its audiovisual context, images from their surrounding discourse, and statistical patterns from the original materials through which their social meaning was produced.
This HSSH Brown Bag presentation introduces Datascene, a developing research infrastructure and computational method for analysing heterogeneous and multimodal materials as structured research data. Datascene is designed to support video, audio recordings, textual documents, individual photographs, websites and pre-existing multimodal research corpora. It brings together speech and language processing, computer vision, temporal analysis, semantic metadata, machine learning, statistical methods and computational social-science approaches.
Audiovisual material provides the project’s principal methodological case because video combines temporal, visual, auditory, textual and narrative evidence within the same source. The underlying method is nevertheless more general: observations from different materials and modalities are represented as mutually addressable, inspectable and comparable analytical objects while maintaining transparent links to their original sources.
The associated method paper asks how qualitative and narrative analysis can be computationally operationalized and scaled without detaching theoretical concepts from source evidence or transferring interpretive authority entirely to automated systems. Datascene approaches actors and agencies, events, relations, narrative developments and other theoretically informed concepts as source-bound analytical objects. Computational systems may detect, organize, compare and propose connections among evidence, while researchers retain authority to inspect, correct, confirm, reject and interpret the resulting propositions.
The presentation will discuss several dimensions of scalability: analysis across larger corpora, movement between different analytical levels, integration of multiple modalities and material types, comparison across sources, and reuse of confirmed observations across analytical procedures. It will also consider the methodological distinction:
Observation ≠ measurement ≠ candidate interpretation ≠ confirmed interpretation ≠ research claim.
The broader objective is to establish scalable and reproducible workflows for research-grade multimodal analysis while preserving human interpretability, theoretical plurality and methodological traceability. Datascene is intended to support research in the social sciences, humanities, communication, media studies and related fields, as well as the analysis of heterogeneous digital collections held by cultural and memory institutions. Future large-scale processing is planned through CSC computing infrastructure.
The session is particularly recommended for researchers interested in the use of artificial intelligence, machine learning and statistical methods in qualitative research. No specialist technical background is required. Participants are invited to consider how computational methods might extend interpretive research without displacing its theoretical foundations or the researcher’s analytical judgment.
Petteri Laine is a PhD researcher in Computational Social Sciences with more than 20 years of experience in media, communications, and creative industry management. He combines extensive industry expertise with solid computational and analytical research skills. He is the research lead of Datascene and has a clear vision for its development. Laine is writing his thesis about the emergence of the self-determined data subject in the faculty of social sciences of the University of Helsinki.
Jukka Kortti is a social science historian at the University of Helsinki. He holds the title of docent (associate/adjunct professor) at the University of Helsinki and Aalto University. His research interests focus on media history and intellectual history. He has recently directed a research project on the history of the Finnish public broadcasting company Yle (Yle100) and has published widely on media history, including textbooks and peer-reviewed theoretical contributions in leading journals of the field. He is currently preparing a monograph on historical documentary films for Palgrave Macmillan.
Reko Elovainio is a PhD researcher in Social Psychology with more than 10 years of experience in related fields. His expertise lies in Computational Social Science methodologies and the application of virtual reality technologies in social psychological research. Elovainio has strong understanding of the challenges in managing video data.
Do Young Men and Women Really Differ More Than Before?
Recent media discussions have suggested that young men and women are drifting apart in their worldviews. In this presentation, I present a paper that examined whether such claims hold up using European Social Survey data from 2002 to 2023, covering 34 countries. I ask whether gender gaps in values are larger in more gender-equal countries and whether they have widened over time, especially among younger people (aged 18-29).
The short answer is: not really. Across countries and over time, the evidence does not support the idea that men’s and women’s values are increasingly diverging. If anything, the overall gender difference was slightly smaller in 2023 than in 2002, although the overall time trends for men and women were both weak as well as heterogeneous across countries. Analyses focusing on younger respondents and single countries also did not show the kind of widening youth gender gap often implied in public debate.
Beyond the empirical findings, the presentation reflects on how knowledge about social trends is produced in an era where publicly available survey data are easy to analyze and visualize. Data journalism can raise important questions, but it often operates with largely uncontrolled analytical degrees of freedom and strong incentives to report striking patterns rather than null results. Social science faces similar temptations, but also has tools such as preregistration, transparent reporting, and clearer distinctions between exploratory and confirmatory research. This case illustrates why those tools matter: sometimes the most important finding is that the headline story is not happening.
Ville-Juhani Ilmarinen is a university researcher at the Department of Education, University of Helsinki. His research and teaching focuses on statistical methods and metascience. His work has explored topics such as how personal values relate to parenthood and voting, psychological similarity between close individuals, political polarization, personality, political ideology and health behavior, and gender differences from a cross-cultural perspective.