Better tools to support research, benefit from Big Data, and develop new methodologies - the unique mandate of HSSH's new multidisciplinary team
The Methodological Unit of the Helsinki Institute of Humanities and Social Sciences (HSSH) develops research methods using new opportunities provided by digital data.

Four experts in different research data and methods have started work at the HSSH Methodological Unit. Their role is to develop new research methods and support research teams at University of Helsinki’s city centre campus in issues related to data management, research methods and infrastructure. The new Methodological Unit is unique in humanities and social sciences in Finland, where there is no other group with such a broad mission.

The multidisciplinary team is composed of researchers Sointu Leikas, Heta Moustgaard, Jouni Tuominen and Matti Pohjonen. The Methodological Unit has been assembled so that their specialties and competencies complement each other. According to a recent HSSH survey report, SSH researchers ask for better support to enable them to take advantage of new research opportunities in the digital environment. It is precisely this need that the Methodological Unit hopes to address.

Test subject research and experimental data – ideas to improve humanities and social sciences

Extensive behavioral data is difficult to capture, so combining digital technology with behavioral research inspires psychology researcher Sointu Leikas. She already has ideas how to take forward this inspiration at HSSH.

First of all, Leikas is concerned that people do not participate in studies anymore in sufficient numbers (e.g. Galea & Tracy 2007), which means that the samples are often too small and unrepresentative. This change is illustrated by the fact that in the 1970s and 1980s, the U.S. participation rate in phone surveys was about 70 percent. Today, according to some estimates, the participation rate is only 5–10% (Curtin et al. 2005; De Heer & De Leeuw 2002; Kennedy & Hartig 2019).

– People are clearly less willing to participate in the research and representativeness has collapsed. That five percent will inevitably form a selective group, says Sointu Leikas.

To improve the situation, Leikas is interested in developing a comprehensive register of research subjects who researchers could invite to participate and to obtain anonymized research data. She is also aware that creating such a comprehensive registry can be challenging. Not only are there many issues related to security and technology that need to be addressed, people also need to be motivated to participate and the register needs to be diverse enough so that the material remains rich year after year. However, new digital methods might provide a solution to these challenges.

Another idea Leikas has been toying around with is an application that captures experiental data. The idea behind this application is that subjects can easily fill in information about how they have felt in different situations and after meeting specific people. Researchers, in turn, would receive anonymized data for scientific research. Cross-analyzing data on subjects’ feelings, behavior, situations, human contacts, and time and place could thus provide new insights into people’s everyday behavior.

Well-being companies already use apps that allow customers to self-evaluate themselves. The idea behind Leikas’s application would be different from these in that it would be free, at least at the launching stage, and it would be based on top-level behavioral psychological research. Subjects would be motivated to participate through receiving free research-based assessment on their activities and behavior. In the best-case scenario, research subjects would also receive a tax-free financial reward for participating.

– People today are very interested in knowing more about themselves. At the same time, this could promote science as well, says Sointu Leikas.

Building bridges between people and computers

Jouni Tuominen, a computer scientist by training, specializes in solving humanities and social sciences research questions by using computational methods. In a way, Tuominen is exactly the kind of expert that Sointu Leikas might need to take her application idea forward.

– For the machine, text is just text, that is, it does not itself understand what the text is trying to signify or what the meanings are that form the text. I try to clarify to the machine what the text is about, so that the machine can form deeper connections based on meaning in the text, Tuominen describes his expertise.

At HSSH, Tuominen is interested especially in developing digital research practices and tools that allow researchers to describe more accurately and practically how the analysis has been done. Open science requires that researchers can clearly explain how data has been collected, changed and enriched, and how this research has progressed step by step.

– The research process must be written in an open manner, this is central to scientific practice itself, says Tuominen. Tuominen hopes to contribute to increasing researchers' data literacy skills to facilitate this.

Aiming for multidisciplinary methodological development

Demographer Heta Moustgaard considers it important to enhance the understanding and use of causal methods in social science research. She has worked extensively with register data and believes that new developments in traditional quantitative methods can also be useful for new Big Data methods.

– Researchers have already struggled with many fundamental problems regarding data representativeness and causality. This can be useful when we talk with social scientists working with Big Data, says Heta Moustgaard.

Moustgaard hopes that the HSSH will be able to promote multidisciplinary discussions and collaboration which can help research teams discover new research methods and improve the one’s they are already using.

There is a need for more fundamental debates in humanities and social sciences

During his career, Matti Pohjonen has adopted new perspectives and methods. He is fascinated by pioneering multidisciplinary methodological development and he has been involved in research projects that have, for instance, used dynamic network analysis, visual analysis, and experimental artificial intelligence art.

Pohjonen is enthusiastic about the possibilities provided by digital methods but is also concerned if the more philosophical considerations and ethical issues are obviated by technological development.

– The problem is too important to be left only to ones who already know how to use computational methods or develop AI. More critical humanistic and social science debate is needed, says Pohjonen.

In his aspirations, HSSH is a recognised institute that develops innovative research methods in collaboration with international stakeholders. In the best-case scenario, according to Pohjonen, HSSH could also develop research cooperation and methodological development in the future outside classical humanities and social sciences research, for instance with natural sciences, medicine and technical sciences.


Curtin, R., Presser, S., & Singer, E. (2005): Changes in telephone survey nonresponse over the past quarter century. Public opinion quarterly, 69(1), 87–98.
Galea, S., & Tracy, M. (2007): Participation rates in epidemiologic studies. Annals of epidemiology, 17(9), 643–653.
De Heer, W., & De Leeuw, E. (2002): Trends in household survey nonresponse: A longitudinal and international comparison. Survey nonresponse, 41, 41–54.
Kennedy, C. & Hartig, H. (2019): Response rates in telephone surveys have resumed their decline. Pew Research Center.