publications

2026

1. How Empathy and Partisanship Affected Attitude Changes Following the Assassination of Shinzo Abe: Evidence from Panel Surveys

   Zeyu Lyu and Susumu Cato

   Public Opinion Quarterly, 2026

   Forthcoming

2024

1. Polarization of Opinion

   Zeyu Lyu, Kikuko Nagayoshi, and Hiroki Takikawa

   In Sociological Foundations of Computational Social Science, 2024

   Abs DOI

   Opinion polarization is increasingly attracting attention due to its potential to disrupt societies. While the issue is becoming more prominent, the concept of opinion polarization remains intricate, encompassing various mechanisms of formation and context-dependent factors. Consequently, the mechanism of opinion polarization has yet to be conclusively demonstrated. Recently, the proliferation of digital data, combined with an array of computational methods, is providing new opportunities to investigate the nuances of opinion polarization. In order to better understand the cutting-edge and innovative works occurring in this field, this chapter will (1) clarify the concept of opinion polarization and distinguish its different variants for theoretical clarity, (2) provide an overview of primary novel data and methods closely related to the investigation of opinion polarization, (3) review several representative research to demonstrate how novel data and advanced method can be applied to address both theoretical and practical questions in research of opinion polarization, and (4) discuss how to integrate theoretical concepts and empirical findings to establish an iterative research framework of opinion polarization.

2023

1. Cross-Cutting Interaction, Inter-Party Hostility, and Partisan Identity: Analysis of Offensive Speech in Social Media

   Zeyu Lyu

   New Media & Society, 2023

   Abs DOI

   This study utilizes social media data and deep-learning-based text classification methods to investigate cross-cutting interactions on social media. Our findings reveal that people are more likely to use offensive speech in response to content published by opposing partisans. Furthermore, we demonstrate how inter-party hostility is associated with the partisan identity of both the message sender and the target in the interaction. On one hand, the findings indicate that strong partisans and people who publicly assert their partisan identities tend to attack opposing partisans, suggesting a relationship between the salience of partisan identity and value defense mechanisms. On the other hand, strong partisans, especially politicians, are more likely to be the target of offensive speech from opposing partisans. The disparity in the extent of received offensive speech is argued to result from individuals? tendency to maintain their partisan identification by expressing hostility toward representative individuals of opposing partisans.

2. Digitization of Weather Records of Seungjeongwon Ilgi: A Historical Weather Dynamics Dataset of the Korean Peninsula in 1623–1910

   Zeyu Lyu, Kohei Ichikawa, Yongchao Cheng, and 2 more authors

   Geoscience Data Journal, Oct 2023

   Abs DOI

   Abstract Historical weather records from Europe indicate that the Earth experienced substantial climate variability, which caused, for instance, the Little Ice Age and the global crisis in the period between the 14th and 19th centuries. However, it is still unclear how global this climate variability was because of the scarce meteorological data availability in other regions including East Asia, especially around the 17th century. In this context, Seungjeongwon Ilgi, a daily record of the Royal Secretariat of the Joseon Dynasty of Korea, is a precious source of historical meteorological records for the Korean Peninsula, as it covers 288?years of weather observations made during 1623?1910. We used the digital database of Seungjeongwon Ilgi to construct a machine-readable weather condition dataset. To this end, we extracted valid weather information from the original weather description text and compiled them into pre-defined weather categories. Additionally, we attempted to improve the usability of dataset by converting the reported dates in the traditional calendar system to those in the Gregorian calendar. Finally, we outlined promising implications of this dataset for meteorological and climatological studies, while describing the limitations of the dataset. Overall, future studies focusing on the climate and weather of the past could use this meteorological database for investigating long-term climate variability. Our datasets are publicly available at 10.5281/zenodo.8382243.

2022

1. Media Framing and Expression of Anti-China Sentiment in COVID-19-related News Discourse: An Analysis Using Deep Learning Methods

   Zeyu Lyu and Hiroki Takikawa

   Heliyon, Oct 2022

   Abs DOI

   This study focuses on news content related to China and COVID-19 during the COVID-19 pandemic and investigates how media frame, affected the emergence of anti-China sentiments through a case study of Japanese online news discourse. We collected large-scale digital trace data including online news and comments during the COVID-19 pandemic. By employing deep learning-based sentiment classifications, we were able to measure the extent of anti-China sentiments expressed through comments during the pandemic’s different phases and on different types of news content. Our results provide empirical evidence that the news media’s negative depictions of China and coverage related to political and international relations issues increased as the prevalence of COVID-19 in Japan increased. Importantly, since this coverage can prompt the expression of anti-China sentiment, we argue that the framing used by the media can provide discursive contexts that escalate COVID-19 issues into a broader expression of anti-China sentiment. This study not only identifies the impact of media frames on the expression of anti-China sentiment but also contributes to the development of methods for detecting public opinion and measuring the framing effect with big data and advanced computational tools.

2. The Disparity and Dynamics of Social Distancing Behaviors in Japan: Investigation of Mobile Phone Mobility Data

   Zeyu Lyu and Hiroki Takikawa

   JMIR Medical Informatics, Mar 2022

   Abs DOI

   Background: The availability of large-scale and fine-grained aggregated mobility data has allowed researchers to observe the dynamics of social distancing behaviors at high spatial and temporal resolutions. Despite the increasing attention paid to this research agenda, limited studies have focused on the demographic factors related to mobility, and the dynamics of social distancing behaviors have not been fully investigated. Objective: This study aims to assist in designing and implementing public health policies by exploring how social distancing behaviors varied among various demographic groups over time. Methods: We combined several data sources, including mobile tracking mobility data and geographical statistics, to estimate the visiting population of entertainment venues across demographic groups, which can be considered the proxy of social distancing behaviors. Next, we used time series analysis methods to investigate how voluntary and policy-induced social distancing behaviors shifted over time across demographic groups. Results: Our findings demonstrate distinct patterns of social distancing behaviors and their dynamics across age groups. On the one hand, although entertainment venues’ population comprises mainly individuals aged 20-40 years, a more significant proportion of the youth has adopted social distancing behaviors and complied with policy implementations compared to older age groups. From this perspective, the increasing contribution to infections by the youth should be more likely to be attributed to their number rather than their violation of social distancing behaviors. On the other hand, although risk perception and self-restriction recommendations can induce social distancing behaviors, their impact and effectiveness appear to be largely weakened during Japan’s second state of emergency. Conclusions: This study provides a timely reference for policymakers about the current situation on how different demographic groups adopt social distancing behaviors over time. On the one hand, the age-dependent disparity requires more nuanced and targeted mitigation strategies to increase the intention of elderly individuals to adopt mobility restriction behaviors. On the other hand, considering that the effectiveness of policy implementations requesting social distancing behaviors appears to decline over time, in extreme cases, the government should consider imposing stricter social distancing interventions, as they are necessary to promote social distancing behaviors and mitigate the transmission of COVID-19.

2020

1. Trust, Risk Perception, and COVID-19 Infections: Evidence from Multilevel Analyses of Combined Original Dataset in China.

   Maoxin Ye and Zeyu Lyu

   Social Science & Medicine, Mar 2020

   Abs DOI

   Previous studies have revealed medical, democratic, and political factors altering responses to unexpected infectious diseases. However, few studies have attempted to explore the factors affecting disease infection from a social perspective. Here, we argue that trust, which plays an important role in shaping people’ s risk perception toward hazards, can also affect risk perception toward infections from a social perspective. Drawing on the indication that risk perception of diseases helps prevent people from being infected by promoting responsible behaviors, it can be further asserted that trust may alter the infection rate of diseases as a result of risk perception toward infectious diseases. This is an essential point for preventing the spread of infectious diseases and should be demonstrated. To empirically test this prediction, this study uses the COVID-19 outbreak in China as an example and applies an original dataset combining real-time big data, official data, and social survey data from 317 cities in 31 Chinese provinces to demonstrate whether trust influences the infection rate of diseases. Multilevel regression analyses reveal three main results: (1) trust in local government and media helps to reduce the infection rate of diseases; (2) generalized trust promotes a higher rather than lower infection rate; and (3) the effects of different types of trust are either completely or partly mediated by risk perception toward diseases. The theoretical and practical implications of this study provide suggestions for improving the public health system in response to possible infectious diseases.

2. Ideological and Behavioral Perspectives on Political Polarization: Evidence from Japan.

   Zeyu Lyu

   Sociological Theory and Methods, Mar 2020

   DOI

2019

1. Towards an Understanding of Online Extremism in Japan

   Zeyu Lyu

   In IEEE/WIC/ACM International Conference on Web Intelligence - Companion Volume, Mar 2019

   Abs DOI

   Using a large amount of social media data, this study employed a variety of computational methods to investigate online extremism in Japan. In order to explain the increase of online extremism, this study identifies extremists by estimating the ideological position of social media users based on the follower-followee relationship. Following this, this study characterizes the behavioral patterns of such individuals from two perspectives: comparison of profile information and preference in online discussions among different ideological groups.Computational methods provide many insights into the online extremism in Japan. First, this study finds that although online extremism has been frequently debated about in the recent years, it is somewhat surprising there were a relatively limited number of extremists. Moreover, this study finds that such individuals are more likely to spread information and express their views than moderate users. They particularly exhibit a significant preference to engage in discussions related to political issues or social issues. As a consequence, their behavior and views are more likely to capture a lot of attention and generate influence as a consequence. Taken together, the findings in this study suggest that online extremism in Japan is attributed to the behavioral patterns of extremists, rather than their increasing number.