Understanding what would happen when something was changed, introduced, or removed plays a key role in discussing, designing, and planning future societies. The use of advanced technologies and data enables us to analyze as many scenarios as possible before implementing policies or introducing infrastructures in urban spaces to see how these changes will affect cities and towns. We address the following research questions in order to make such solutions more equitable, diverse, and inclusive for broader cities and towns: (1) how to design participatory structures through digital solutions in cities and villages, (2) how to simulate human behavior changes in cities and villages with considering socio-economic heterogeneity, and (3) how to estimate and evaluate human behavior changes in urban spaces.
Selected published works
This research is supported by JSPS KAKENHI Grant-in-Aid for Early-Career Scientists, Grant Number JP21K13278.
With critical perspectives, the research empirically explores how digital media and data facilitate a democratic participatory structure for sustainability transitions in cities.
Selected published works
Shibuya, Yuya, Hamm, Andrea, & Cerratto Pargman, Teresa. (2022). Mapping HCI Research Methods for Studying Social Media Interaction: A Systematic Literature Review. Computers in Human Behavior, 129, 107131.
Shibuya, Yuya, Hamm, Andrea, Raetzsch, Christoph. (2021). From Data to Discourse: How Communicating Civic Data Can Provide a Participatory Structure for Sustainable Cities and Communities. In Proceedings of the International Sustainable Development Research Society (ISDRS), July 13-15, 2021, Sweden.
Hamm, Andrea, Shibuya, Yuya, Ullrich, Stefan and Cerratto Pargman, Teresa. (2021). What Makes Civic Tech Initiatives To Last Over Time? Dissecting Two Global Cases. In CHI ’21: Proceedings of the 39th Annual ACM Conference on Human Factors in Computing Systems, May 08–13, 2021, Yokohama, Japan. ACM, New York, NY, USA
The study explores the possibility of using social media data for detecting socio-economic recovery activities. In the last decade, there have been intensive research activities focusing on social media during and after disasters. This approach, which views people’s communication on social media as a sensor for real-time situations, has been widely adopted as the “people as sensor” approach. Furthermore, to improve recovery efforts after large-scale disasters, detecting communities’ real-time recovery situations is essential, since conventional socio-economic recovery indicators, such as governmental statistics, are not published in real time. Thanks to its timeliness, using social media data can fill the gap. Motivated by this possibility, the study especially focuses on the relationships between people’s communication on Twitter and Facebook pages, and socio-economic recovery activities as reflected in the used-car market data and the housing market data in the case of two major disasters: the Great East Japan Earthquake and Tsunami of 2011 and Hurricane Sandy in 2012. The study pursues an interdisciplinary approach, combining e.g. disaster recovery studies, crisis informatics, and economics. In terms of its contributions, firstly, the study sheds light on the “people as sensors” approach for detecting socio-economic recovery activities, which has not been thoroughly studied to date but has the potential to improve situation awareness during the recovery phase. Secondly, the study proposes new socio-economic recovery indicators: social media communication data, used-car market data, and housing market data. Thirdly, in the context of using social media during the recovery phase, the results demonstrate the importance of distinguishing people behind communications. The study demonstrates the importance of taking into consideration geological closeness and people's personal relations to the affected areas (i.e., whether communications are posted by people who are at or near disaster-stricken areas and by those who are farther away).
Selected published work