Publications

Book

1. 

   Social Media Communication Data for Recovery

   Yuya Shibuya

   (2020)

   Abs LINK Amazon

   This book 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, this book 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 book pursues an interdisciplinary approach, combining e.g. disaster recovery studies, crisis informatics, and economics. In terms of its contributions, firstly, the book 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 book proposes new socio-economic recovery indicators: 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 between social media data posted both by people who are at or near disaster-stricken areas and by those who are farther away.

Journal & Conference Proceedings

2024

1. Behavioral ChangeSocial Media Interaction

   Emotions, behaviors and places: Mapping sentiments with behaviors in Japanese tweets

   Mingchen Liu, Yuya Shibuya, and Yoshihide Sekimoto

   Cities (2024) 155, 105449

   Abs LINK

   Emotions are the basis of human behavior and an important part of spatial constructions. Despite numerous efforts to leverage spatio-temporal big data from social media to capture public sentiments, there is a lack of understanding of how individuals’ behaviors play a role in people’s sentiments at places they visit. Thus, this study aims to advance our understanding of the complex relationships between sentiments, behaviors, and places. Through a case study in Japan in 2021, we analyzed one year of countrywide geotagged social media by fine-tuning a pre-trained Japanese BERT model (accuracy: 74 %). The results emphasize the importance of understanding user emotions by considering people’s behaviors, even within similar types of locations. Our research framework would be beneficial for urban planners and policymakers to enhance urban spaces.

2. Civic Tech

   Can civic data be counterdata and open data? Exploring the limits of data, contestation, and governance

   Yuya Shibuya, Seyi Olojo, Andrea Hamm, Radhika Krishnan, and Teresa Cerratto Pargman

   In Proceedings of the Weizenbaum Conference 2024 (2024)

   Abs

   The increasing surveillance by big tech companies or/and governments has raised concerns about the democratic and participatory structure in the datafied society. Meanwhile, in the past decade, various bottom-up civic tech and digital civic initiatives have emerged to tackle local pressing issues, such as air pollution and disaster response, often with technology-mediated data collection, curation, analysis, design, and visualisations, promoting democratic participation. In this article, we discuss how these data are understood in diverse contexts beyond the realm of civic tech and digital civics. In doing so, we explore the potentials and limits of civic data by exploring the intersections and differences of civic data from adjacent data-related concepts often used in civic tech communities by themselves: counterdata and open data. Through our discursive exploration of these three data concepts, we identified that there is a limited understanding of what data are “civic,” the questions of the power structure, diversity and inclusion, and infrastructuring civic data have been discussed less.

3. Behavioral Change

   Assessing internal displacement patterns in Ukraine during the beginning of the Russian invasion in 2022

   Yuya Shibuya, Nicholas Jones, and Yoshihide Sekimoto

   Scientific Reports (2024) 14:11123

   Abs LINK

   Given the worldwide increase of forcibly displaced populations, particularly internally displaced persons (IDPs), it’s crucial to have an up-to-date and precise tracking framework for population movements. Here, we study how the spatial and temporal pattern of a large-scale internal population movement can be monitored using human mobility datasets by exploring the case of IDPs in Ukraine at the beginning of the Russian invasion of 2022. Specifically, this study examines the sizes and travel distances of internal displacements based on GPS human mobility data, using the combinations of mobility pattern estimation methods such as truncated power law fitting and visualizing the results for humanitarian operations. Our analysis reveals that, although the city of Kyiv started to lose its population around 5 weeks before the invasion, a significant drop happened in the second week of the invasion (4.3 times larger than the size of the population lost in 5 weeks before the invasion), and the population coming to the city increased again from the third week of the invasion, indicating that displaced people started to back to their homes. Meanwhile, adjacent southern areas of Kyiv and the areas close to the western borders experienced many migrants from the first week of the invasion and from the second to third weeks of the invasion, respectively. In addition, people from relatively higher-wealth areas tended to relocate their home locations far away from their original locations compared to those from other areas. For example, 19 % of people who originally lived in higher wealth areas in the North region, including the city of Kyiv, moved their home location more than 500 km, while only 9 % of those who originally lived in lower wealth areas in the North region moved their home location more than 500 km.

4. Social Media Interaction

   AI Optimism, Pessimism, or Indifference? Challenges of Combating AI-Made Misinformation Under Mixed Perceptions of AI

   Yuya Shibuya, Tomoka Nakazato, and Soichiro Takagi

   In Proceedings of the ICWSM Workshops (2024)

   Abs LINK

   There is growing concern about misinformation and propaganda being spread through AI-generated content that is often indistinguishable from human-made content. As a response, major platforms (e.g., Google, Meta, TikTok) have introduced policies to warn users of AI-generated content. One potential challenge here is the divergent perceptions of AI in the public may cause different reactions to such warnings. While some see AI’s potential benefits for society, others are more pessimistic about the potential risks. It is not yet clear how these polarized attitudes affect efforts to combat misinformation. Our experimental study investigated how people’s attitudes toward AI influenced their perceptions of AI-generated posts. In our experiment, participants were asked to report what factors influenced their judgments about the accuracy of AI-generated video content in an open-ended response format. The study found that most participants relied on their pre-existing knowledge and beliefs to evaluate AI-generated posts, even when shown a warning message to AI-made contents. Interestingly, some participants mindlessly evaluated the accuracies of all of the videos positively or negatively based on their positive or negative beliefs about AI. The finding suggests that incorporating a simple warning with GenAI-made content may be insufficient and has varying effects on users, ranging from underestimated to no reactions to overestimated reactions.

5. 

   Nationwide synthetic human mobility dataset construction from limited travel surveys and open data

   Takehiro Kashiyama, Yanbo Pang, Yuya Shibuya, Takahiro Yabe, and Yoshihide Sekimoto

   In Computer-Aided Civil and Infrastructure Engineering (2024)

   LINK
6. Civic Tech

   What Does ’Failure’ Mean in Civic Tech? We Need Continued Conversations About Discontinuation

   Andrea Hamm, Yuya Shibuya, Teresa Cerratto Pargman, Roy Bendor, Christoph Raetzsch, Mennatullah Hendawy, Rainer Rehak, Gwen Klerks, Ben Schouten, and Nicolai Brodersen Hansen

   Interactions (2024) 31:2, 34–38

   LINK
7. Behavioral Change

   Social segregation levels vary depending on activity space types: Comparison of segregation in residential, workplace, routine and non-routine activities in Tokyo metropolitan area

   Chenchen Sun, Yuya Shibuya, and Yoshihide Sekimoto

   Cities (2024) 146:2, 104745

   Abs LINK

   Given the dynamic spatial characteristics of modern cities, the issue of social segregation based on activity spaces has been gaining increased attention. However, few studies have performed a detailed comparison of the differences in social segregation at different types of activities space on the citywide scale with a relatively small granularity from both place and individual perspectives. To gain a better understanding of the intricate and dynamic aspects of human mobility and its patterns of segregation, it is necessary to conduct comparative research utilizing several activity segregation indices by exploring different contexts behind people’s activities. Thus, in this study, we take the Tokyo metropolitan area as a case and classify the activity spaces into four categories: residential, working, routine activities, and non-routine activities, and then calculate the place income segregation and individual experienced income segregation under different activity contexts. Our findings show that the segregation levels vary depending on the activity contexts. For the place income segregation, the segregation level in residential and non-routine activity spaces tends to be lower than that in the working and routine activity spaces, respectively. In terms of spatial distribution, the values of segregation indicators in the suburbs deviate more from the regional mean. In addition, the main composition of the population in highly segregated areas is low- and middle-income class groups, and there are no super-rich activity areas that completely exclude other income groups in the Tokyo metropolitan area. For the individual experienced income segregation, the higher the household income, the lower the segregation level among all households except the poorest. Furthermore, the differences between individual income segregation indicators tend to be smaller near the central area and bigger in suburban areas. This work demonstrates the importance of comparing the differences in various activity segregation contexts in urban spaces instead of merely focusing on one specific perspective.

8. Behavioral Change

   Enhancing geospatial retail analysis by integrating synthetic human mobility simulations

   Santiago Garcia-Gabilondo, Yuya Shibuya, and Yoshihide Sekimoto

   Computers, Environment and Urban Systems (2024) 108:2, 102058

   Abs LINK

   The accuracy of retail location models depends on their precise calibration, but the data necessary for such a key task is seldom available. In this research, we use synthetic human mobility data, which introduces commuting dynamics, to improve the reliability of such models. We use the origin-destination flows to distribute households’ potential expenditures in their home and commuting locations with the aim of modeling non-residential-driven demand in the commercial streets of Tokyo. We estimate potential revenues of commercial streets using the Huff model with its conventional specification as well as a variation of it that adopts pedestrian trajectory counts as the deterrence variable. We found that redistributing the potential expenditures toward the households’ daytime locations significantly increased the model’s performance. Additionally, we found that our use of pedestrian trajectory counts is comparable to using distance within the Huff model framework, but our proposed model was still outperformed by the conventional Huff model specification. We conclude that combining synthetic human mobility simulations and retail location models significantly increases the reliability of analysis in data-constrained situations.

9. 

   Sustainable and Resilient Societies? Comparing Notions of the ‘Smart City’ in Germany and Japan in Sustainable Societies in a Fragile World. Perspectives from Germany and Japan (Hommerich and Kimura Ed.)

   Andrea Hamm, Yuya Shibuya, and Christoph Raetzsch

   (2024)

   LINK

2023

1. Behavioral Change

   Unmasking Socioeconomic Disparities: A Study of Urban Segregation through the Lens of Mobile App Usage Patterns

   Yuya Shibuya, Santiago Garcia, Sun Chenchen, Yu Peiran, Ma Jue, and Yoshihide Sekimoto

   In Abstracts of Netmob 2023 (2023)

   Netmob 2023 Best Challenge Contribution Runner-up

   Abs LINK

   Human mobility dynamics are interconnected with diversified lifestyles and human behavioral contexts in modern cities. By understanding how digital and real-world lifestyles intersect, we can gain insight into issues such as work-life balance, the divide between physical and digital experiences, and economic disparities in urban living. In this study, we examined mobile app usage data in France to explore how digital lifestyles are connected to urban segregation. Our findings show that app usage relates not only to land use patterns and time and week of days but also to income levels. For example, lower-income places use games and message apps relatively highly compared with higher-income places by 0.6 and 0.3 points, respectively. On the other hand, higher-income places use video call and email apps relatively highly compared with higher-income places by 0.4 points and 0.2 points, respectively. Additionally, our study sheds light on the importance of synchronicity in digital lifestyles in relation to the physical world. We found clusters with a strong synchrony of digital lifestyle. Further investigation on the impacts of socioeconomic and urban function on synchrony is needed.

2. Social Media Interaction

   Characterizing the Behavior of Healthcare Experts Towards COVID-19 Vaccine on Twitter

   Tomoka Nakazato, Yuya Shibuya, and Soichiro Takagi

   In Proceedings of WI-IAT2023 (2023)

   Abs LINK

   Spreading vaccine misinformation can have severe consequences on public health, including the increased risk of disease outbreaks. Even though experts with specialized knowledge can play a crucial role in combating vaccine misinformation, there is a lack of sufficient understanding of how healthcare experts communicated on social media during the early stages of the COVID-19 pandemic. Therefore, this study uses large-scale Twitter data in Japanese to examine how healthcare experts participated in key discussions about vaccines in 2020. By identifying healthcare expert users utilizing the Term Frequency - Inverse Document Frequency (TF-IDF) algorithm on social media profiles, we discover distinctive behaviors of healthcare expert users in vaccine communication. Our findings suggest that healthcare expert users were more likely to be pro-vaccine and less likely to be on the political right or neutral. We also find that healthcare professional users received more replies and had more followers. In addition, healthcare professionals tended to use different types of information sources compared with non-professionals. These findings suggest a unique position of healthcare professional users in social media. This study contributes to considering the role of healthcare experts in present public health policy, where social media has been increasing its presence.

3. Civic Tech

   Mainstreaming civic tech and citizen sensing: a research agenda on co-creation methods, data interfaces, and impact pathways

   Christoph Raetzsch, Andrea Hamm, and Yuya Shibuya

   Frontiers in Environmental Science (2023) 1228487:11

   LINK
4. Civic Tech

   Failed yet successful: Learning from discontinued civic tech initiatives

   Andrea Hamm, Yuya Shibuya, Teresa Cerratto Pargman, Roy Bendor, Nicolai Brodersen Hansen, Christoph Raetzsch, Masahiko Shoji, Christoph Bieber, Mennatullah Hendawy, Gwen Klerks, and Ben Schouten

   In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems (CHI EA ’) (2023)

   Abs LINK PDF Website

   The design of civic tech is often confronted with impediments, barriers, and a lack of resources. These and other causes may lead to the discontinuation and even abandonment of initiatives. Since seemingly failed projects are much more difficult to publish as articles, this workshop will provide academics and practitioners with a rare opportunity to exchange experiences and insights on discontinued civic tech initiatives. The goal of the workshop is to develop a better understanding of why some civic tech initiatives fail and ask whether discontinued initiatives may still somehow contribute to social change and the growth of digital civics. A variety of subquestions around discontinued civic tech will be addressed in the workshop, including matters of participation, citizen science, public management, power structures and biases, and communication.

5. Russo-Ukrainian War on Facebook: A Temporal and Spatial Study Based on BERTopic modeling

   Kai-Yi Tan, Chun-Ming Lai, Yin-Jie Foo, and Yuya Shibuya

   In Proceedings of International Conference on Security and Information Technologies with AI, Internet Computing and Big-data Applications (SITAIBA 2023) (2023)

2022

1. Behavioral ChangeCivic Tech

   Do open data impact citizens’ behavior? Assessing face mask panic buying behaviors during the COVID-19 pandemic

   Yuya Shibuya, Chun-Ming Lai, Andrea Hamm, Soichiro Takagi, and Yoshihide Sekimoto

   Scientific Reports (2022) 12:1, 17607

   Abs LINK PDF

   Data are essential for digital solutions and supporting citizens’ everyday behavior. Open data initiatives have expanded worldwide in the last decades, yet investigating the actual usage of open data and evaluating their impacts are insufficient. Thus, in this paper, we examine an exemplary use case of open data during the early stage of the Covid‐19 pandemic and assess its impacts on citizens. Based on quasi‐experimental methods, the study found that publishing local stores’ real‐time face mask stock levels as open data may have influenced people’s purchase behaviors. Results indicate a reduced panic buying behavior as a consequence of the openly accessible information in the form of an online mask map. Furthermore, the results also suggested that such open‐data‐based countermeasures did not equally impact every citizen and rather varied among socioeconomic conditions, in particular the education level.

2. Social Media Interaction

   Mapping HCI research methods for studying social media interaction: A systematic literature review

   Yuya Shibuya, Andrea Hamm, and Teresa Cerratto Pargman

   Computers in Human Behavior (2022) 129:1, 107131

   Abs LINK PDF

   In the last decades, researchers in Human-computer interaction (HCI) took numerous efforts to investigate people’s social media interaction. To understand how researchers in HCI have studied social media interaction, we examined 149 peer-reviewed articles published between 2008 and 2020 in major HCI conference proceedings and journals. We systematically reviewed the methodologies HCI researchers applied, the research topics these methods covered, and the types of data collected. Through the analysis, we make three contributions: We (1) pinpoint the topic trends by identifying three phases in the study of social media interaction in HCI. Namely, the early phase (2008–2012) focused on user behavior, the growing phase (2013–2016), focused on privacy and health, and the latest phase (2017–2020) focused on design. (2) We map methodological trends in the study of social media interaction in HCI. We also illustrate the trends in relation to the types of data collected in the selected works and, (3) identify underexplored study areas.

2021

1. Civic Tech

   What Makes Civic Tech Initiatives To Last Over Time? Dissecting Two Global Cases

   Andrea Hamm, Yuya Shibuya, Stefan Ullrich, and Teresa Cerratto Cerratto Pargman

   In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (2021) :1, 1–17

   Abs LINK PDF

   Civic tech initiatives dedicated to environmental issues have become a worldwide phenomenon and made invaluable contributions to data, community building, and publics. However, many of them stop after a relatively short time. Therefore, we studied two long-lasting civic tech initiatives of global scale, to understand what makes them sustain over time. To this end, we conducted two mixed-method case studies, combining social network analysis and qualitative content analysis of Twitter data with insights from expert interviews. Drawing on our findings, we identified a set of key factors that help the studied civic tech initiatives to grow and last. Contributing to Digital Civics in HCI, we argue that the civic tech initiatives’ scaling and sustaining are configured through the entanglement of (1) civic data both captured and owned by the citizens for the citizens, (2) the use of open and accessible technology, and (3) the initiatives’ public narrative, giving them a voice on the environmental issue.

2. Civic Tech

   From Data to Discourse: How Communicating Civic Data Can Provide a Participatory Structure for Sustainable Cities and Communities

   Yuya Shibuya, Andrea Hamm, and Christoph Raetzsch

   In International Sustainable Development Research Society Conference (2021)

   Abs LINK PDF

   This study explores how Civil Society Organizations (CSOs) have leveraged civic data to facilitate democratic participatory structure for sustainability transitions around the case of bicycle counters in three US cities over a ten-year period (Seattle, San Francisco, Portland). We identified that CSOs have played crucial roles in public discourse by (1) sustaining long-term public issues through shaping affective as well as analytical discourses and (2) fostering citizens’ sense of ownership and contributions toward sensor devices and the data they generate by contextualizing them through local civic life as well as connecting issues to actors in other cities.

2020

2019

1. Crisis Informatics

   Detecting Disaster Recovery Activities via Social Media Communication Topics.

   Yuya Shibuya, and H. Tanaka

   In the 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) (2019) , 706-718

   LINK PDF
2. Crisis Informatics

   How does a large-scale disaster impact on the used-car market? A case study of the Great East Japan Earthquake and Tsunami

   Yuya Shibuya, and H. Tanaka

   International Journal of Economic Policy Studies (2019) 13:1, 89–117

   The academic award of the Japan Economic Policy Association [Junior award]

   LINK PDF
3. Crisis Informatics

   Using Social Media to Detect Socio-Economic Disaster Recovery

   Yuya Shibuya, and H. Tanaka

   IEEE Intelligent Systems (2019) 34:3, 29–37

   LINK
4. Crisis Informatics

   Socio-Economic Disaster Recovery Captured by Big Housing Market Data

   Yuya Shibuya, and H. Tanaka

   In 2019 IEEE Global Humanitarian Technology Conference (GHTC) (2019) :3, 1–8

   In: 2019 IEEE Global Humanitarian Technology Conference (GHTC) (IEEE)

   ISBN: 978-1-72811-780-5

   LINK

2018

1. Crisis Informatics

   Public Sentiment and Demand for Used Cars after A Large-Scale Disaster: Social Media Sentiment Analysis with Facebook Pages

   Yuya Shibuya, and H. Tanaka

   In Proceedings of the 5th International Workshop on Social Web for Disaster Management (SWDM’18) (2018) :3, 6

   arXiv PDF
2. Crisis Informatics

   A Statistical Analysis Between Consumer Behavior and a Social Network Service: A Case Study of Used-Car Demand Following the Great East Japan Earthquake and Tsunami of 2011

   Yuya Shibuya, and H. Tanaka

   The Review of Socionetwork Strategies (2018) 12:2, 205–236

   LINK

2017

1. Crisis Informatics

   Mining social media for disaster management: Leveraging social media data for community recovery

   Yuya Shibuya

   In 2017 IEEE International Conference on Big Data (Big Data) (2017) :2, 3029–3036

   In: 2017 IEEE International Conference on Big Data (Big Data) (IEEE)

   ISBN: 978-1-5386-2715-0

   LINK
2. Civic Tech

   Impact of ICT tools on disaster logistics issues: A case study of the great east Japan earthquake and Tsunami of 2011

   Yuya Shibuya

   International Journal of Business and Information (2017) 12:3, 310–341

   LINK
3. Civic Tech

   A Typology For ICT-Facilitated Citizen Coproduction: Pre- and Post-Disaster

   Yuya Shibuya

   International Journal of Cyber Society and Education (2017) 10:2, 65–86

   LINK

Presentations

2024

1. Behavioral Change

   Generation gaps in activity space segregations: A case study of Tokyo metropolitan areas using human mobility GPS data

   Chenchen Sun, Yuya Shibuya, and Yoshihide Sekimoto

   In Proceedings of NetMob 2024 (2024)
2. Behavioral Change

   Socioeconomic Disparities in Heat Exposure and Mitigation Based on Human Mobility in India

   Jue Ma, Santiago Garcia Gabilondo, Carl D. Torbjörnsson, Chenchen Sun, Zeyu Wu, Yuya Shibuya, and Yoshihide Sekimoto

   In Proceedings of NetMob 2024 (2024)
3. Behavioral Change

   Dynamic Air Pollution Exposure Index Using Human Mobility Patterns: Case Studies from the Global South

   Yuya Shibuya, Santiago Garcia Gabilondo, Carl D. Torbjörnsson, Zeyu Wu, Chenchen Sun, Jue Ma, and Yoshihide Sekimoto

   In Proceedings of NetMob 2024 (2024)
4. Civic Tech

   Civic Data: Building Democratic Participation through Civic Tech in the Age of Data Capitalism

   Yuya Shibuya

   In Symposium Creating Impact with Data Journalism: Pathways to Civic Communication and Engagement (2024)

   LINK

2023

1. Social Media Interaction

   Good News or Bad News? Political Social Media Messaging During the Tokyo Olympics

   Etienne Gagnon, Kenneth McElwain, and Yuya Shibuya

   In JPOSS (2023)

   LINK

2022

1. Civic Tech

   Insights on sustainability-oriented change in mobility stimulated by civic IoT applications

   Andrea Hamm, Yuya Shibuya, Rainer Rehak, and André Ullrich

   In EJEA International Conference (2022)
2. Social Media Interaction

   How to Do Things with "Values": A Cross-Linguistic Analysis of the Meanings and Functions of a Core Concept on Twitter.

   Avishai Green, Yuya Shibuya, Tommaso Trillo, Saki Mizoroki, Rebecca Scharlach, Blake Hallinan, Tim Park, Effi Levi, Elad Segev, Shaul Shenhav, and Limor Shifman

   In the 2022 Internet Research Conference (AoIR2022) (2022)
3. Civic Tech

   Journalism and the Democratic Interface: From Data Dashboards to Participatory Infrastructures.

   Christoph Raetzsch, Diogo Henriques, Andrea Hamm, and Yuya Shibuya

   In 9th European Communication Conference (ECREA 2022) (2022)
4. Crisis Informatics

   Whose Voices Have We Been Listening to? Opportunities and Challenges of AI for Disaster Management and Resilience.

   Yuya Shibuya

   In BIFOLD Summer School, Ethics in Machine Learning and Data Management (2022)

   Invited Talk
5. Civic Tech

   Towards Digital Twins of Japanese Cities

   Christoph Raetzsch, Diogo Henriques, Andrea Hamm, and Yuya Shibuya

   In Infrastructures of Publics Workshops (2022)

   Invited Talk
6. Civic Tech

   Sustainable or Resilient Societies? Comparing Notions of the "Smart City" between Germany and Japan

   Andrea Hamm, Yuya Shibuya, and Christoph Raetzsch

   In 16th Meeting of the German-Japanese Society for Social Sciences (GJSSS) (2022)
7. Social Media Interaction

   Intertwined Relations between Communication in Cyberspace and Economic and Political Situations in the Physical World.

   Yuya Shibuya

   In Early-Career Scholar Forum, UTokyo Center for Contemporary Japanese Studies (2022)
8. Social Media Interaction

   Good News or Bad News? Political Social Media Messaging during the Olympics.

   Yuya Shibuya

   In Japanese Society for Quantitative Political Science 2022 Winter Meeting (2022)

2020

1. Social Media Interaction

   Factors affecting inbound tourists to Japan: a panel data analysis

   Zhaoyuan Liu, Yuya Shibuya, and Soichiro Takagi

   In Proceedings of the Japan Association for Social and Economic Systems Studies (2020)

2018

1. Crisis InformaticsSocial Media Interaction

   Does Sentiment of Social Media Sense Mid-to Long-Term Socio-Economic Disaster Recovery? A Case Study of Hurricane Sandy Focusing on Housing Demand.

   Yuya Shibuya, and H Tanaka

   In Proceedings of the 17th International Conference of the Japanese Economic Policy Association (Oct. 2018) (2018)
2. Social Media Interaction

   How Does Public Sentiment on Social Media Reflect Socio-Economic Disaster Recovery?

   Yuya Shibuya, and H. Tanaka

   In Poster session presented at the 5th International Conference on Information Communication Technologies for Disaster Management (2018)
3. Social Media Interaction

   Topics of Social Media Communication and Socio-Economic Recovery.

   Yuya Shibuya, and H. Tanaka

   In Poster session presented at ISCRAM ASIA PACIFIC 2018 (2018)

   LINK

2017

1. Crisis Informatics

   A Demand Side Analysis of the Car Market after the Great East Japan Earthquake and Tsunami of 2011: A content analysis of Facebook Pages.

   Yuya Shibuya, and H Tanaka

   In Proceedings of the 16th International Conference of the Japanese Economic Policy Association (2017)