Data, Self and Society
The research group “Data, Self and Society” at the Consumer Society Research Centre explores how datafication, referring to the conversion of aspects of life into quantified data, is promoted, practiced, analyzed and received in the contemporary world. Current research falls under three thematic areas:
Self-tracking and living with data
The rapidly expanding research on wearables and self-tracking practices reflects the rise in the use of digital technology in the everyday. The defining characteristic of self-tracking is that people are confronted with their own personal information, including sleep, steps, stress levels, and eating. Self-tracking relies on personal data streams in an attempt to slice life into comprehensible and controllable units. Life converts into a problem of coding and algorithmic evaluation.
We have studied the Quantified Self and how ordinary people find, or fail to find, value in confrontations with personal data. Recent publications discuss co-evolving with self-tracking technologies, forms of emotion tracking and the situational objectivity characteristic to personal metrics. Demonstrating that the study of data practices and datafication benefits from a more thorough analysis of the everyday, the aim is to critically address the active and ever-changing work around personal data streams. A recently initiated project continues this research by focusing on everyday understandings of algorithms and how civil servants and politicians discuss the role of algorithms in political decision making.
Digital methods and data explorations
Citizen Mindscapes is an open data project in which we contextualize and explore an online forum discussion data (“Suomi24”, in English Finland24), consisting of tens of millions of social media messages over a time span of 15 years. The analysis of large data sets calls for new kind of reflexivity from researchers, including novel research perspectives. In recent publications, we study the datafication of hate and explore the Suomi24-dataset through the concept-metaphor of broken data. We utilize data analytics in an attempt to develop tools and frameworks for understanding how conversational landscapes and topics develop in time. By identifying online practices and engagements, we promote the development and understanding of digital research methods which will allow investigators to gain a more detailed view of the production and analysis of data and deepen the understanding of how temporal aspects of social life, or social media discussions affect, guide, and constrain their participants.
Smarter Social Media Analytics studies and develops methods to identify trends and phenomena using large social media datasets. To this end, we use the full data set of online forum Suomi24 (see above) and the full data set collected and owned by Futusome Oy, covering approximately 1 billion Finnish language messages from different social media services (2001-2016). As a comparative data set we use the representative survey data collected by Taloustutkimus Oy (2007-2016). By cross-investigating these datasets using both computational and qualitative methods, we develop and validate algorithms to identify and explain emerging trends and individual phenomena from the online conversations. Currently we are focusing on various food-related trends. Simultaneously, using an ethnographic approach the project explores how data is used and transformed to knowledge within the data analytics companies, and what are the epistemological considerations that frame data, data analysis methods and visualizations.
Datafied power and digital citizens
The third thematic area explores forms of datafied power and their consequences. We study the evolution of the data economy, datafication of health, and reactions to surveillance economy. The work builds on the notion that software and algorithms produce data and work with it in particular ways and, by doing so, have social, political and economic implications. We follow market developments by exploring the visions and aims of start-up companies and citizen-led co-operatives that aim to modify, with their technologies, platforms and business approaches, the current data economy landscape and forms of digital work. Further research analyses patents related to personal data uses and user/consumer action in relation to personal data management models, from blockchain-based distributed models to dominant US tech-giant models. The project called Becoming Data Citizens explores social and political alternatives that aim at promoting more transparent and citizen-centric data use. We investigate data activism by developing the notion of non-data-centric data activism.
In close collaboration with:
- Janasik-Honkela, N. (2018). Reclaiming Melancholy by Emotion Tracking? Datafication of Emotions in Health Care and at the Workplace. Open Cultural Studies 1(1), 549-558.
- Kristensen, D and Ruckenstein, M. (2018) Co-evolving with self-tracking technologies. New Media and Society.
- Pink, S. Ruckenstein, M. Willim, R. and Duque, M. (2018). Broken data: Conceptualising data in an emerging world. Big Data & Society, 5(1), 2053951717753228.
- Pöyry, E.; Laaksonen, S-M.; Kekkonen, A. & Pääkkönen, J. (2018). Anatomy of Viral Social Media Events. In Proceedings of HICSS’2018, Hawaii, US, January 2018.
- Pantzar M. and Ruckenstein M. (2017): Living the metrics: Self-tracking and situated objectivity. Digital Health. https://doi.org/10.1177/2055207617712590
- Pantzar, M., Ruckenstein, M., & Mustonen, V. (2017). Social rhythms of the heart. Health Sociology Review, 26(1), 22-37.
- Ruckenstein, M. (2017). Keeping data alive: talking DTC genetic testing. Information, Communication & Society, 20(7), 1024-1039.
- Ruckenstein, M. and Pantzar, M. (2017). Beyond the quantified self: Thematic exploration of a dataistic paradigm. New Media & Society, 19(3), 401-418.
- Ruckenstein, M, and M Pantzar, (2015) Datafied life: Techno-Anthropology as a site for exploration and experimentation, Techne, 19 (2): 191-210.
- Pantzar, M. (2017) Kuluttajakansalainen datataloudessa. Tieteessä tapahtuu 35(5): 21-26.
- Ylisiurua, M. (2017). Aihemallinnuksen mahdollisuudet sosiaalisen median aineistojen jäsentämisessä – terveyskeskustelu Suomi24-verkkopalstalla. Kulutustutkimus.Nyt. 11(2), 44-67.
- Janasik-Honkela, N., & Ruckenstein, M. (2016) My Data: Teknologian orjuudesta digitaaliseen vastarintaan. Tieteessä tapahtuu 34(2): 11-19.
- Laaksonen, S-M. (2016). Sosiaalinen media – tutkimusaineiston hankala aarrearkku. Sosiaalilääketieteellinen aikakauslehti 53(2), 145-146. [link]
- Lagus, K., Pantzar, M., Ruckenstein, M. & Ylisiurua, M. (2016) Suomi24: muodonantoa aineistolle. Valtiotieteellisen tiedekunnan julkaisuja 10. Helsinki: Helsingin yliopisto.
- Ruckenstein, M. (2016) Algoritmin valta ja toimittajan vastahanka. In: Maito tappaa ja muita outoja tiedeuutisia. U. Järvi, T. Tammi (eds). Tampere: Vastapaino.
- Lagus, K., Pantzar, M., & Ruckenstein, M. (2015) Keskustelun tunneaallot: Suomi24-hanke. Tieteessä tapahtuu, 33(6):39-41.