Analyzing Social Phenomena and Human Behavior with Information Technology and Big Data.


update:2025/09/12
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Overview of Technology

Computational social science seeks to understand social phenomena and human behavior using advanced computational methods, including machine learning, simulations, and digital experiments. The field covers a wide range of topics—from opinion formation on social media to spatial social segregation, where different social groups are geographically separated—and actively explores new possibilities offered by innovative generative AI technologies, such as large language models. In this term, it aims to contribute both to establishing a new research framework and to solving practical social issues.

Comparison with Conventional Technology

A key advantage of computational social science methods lies in their ability to dynamically and accurately capture complex social phenomena and human behavior, overcoming limitations of traditional social sciences that primarily rely on small-scale surveys and static data.

First, by directly analyzing the vast amounts of behavioral data generated daily, it becomes possible to understand large-scale, high-granularity social processes that were previously difficult to grasp. Second, the use of computational methods allows for the discovery of complex patterns and the structure of new social phenomena that might be overlooked by human intuition or conventional theories alone. Third, by combining simulations and digital experiments, the field has moved beyond mere description and correlation analysis to verifying causal mechanisms and future scenarios.

In this way, computational social science complements traditional methodologies and possesses the advantage of developing social science into a discipline that contributes to solving social problems.

Features and Uniqueness

This field is positioned as a new research framework that integrates social science and information science. It establishes the subject and direction of analysis based on theoretical considerations from social science, then verifies and develops those theories through empirical analysis and simulations that utilize computational techniques and big data.

Practical Application

By leveraging information technology and big data to examine diverse social phenomena and human behavior, the field offers valuable knowledge and expertise for understanding current societal conditions and for designing and evaluating effective intervention strategies.

Keywords

Researchers

Graduate School of Arts and Letters

Lyu Zeyu, Associate Professor