計算社会科学

Computational social science is an approach to elucidating social phenomena through computational methods. In recent years, the accumulation of large-scale data and the accompanying development of mathematical theories have been making it increasingly possible to understand and predict social phenomena that arise from the interactions of diverse individuals. This course focuses on foundational theories such as the statistical properties commonly observed in collective phenomena, data analysis including complex network analysis, statistical modeling, and simulation, while also introducing cutting-edge research on large-scale data analysis in areas such as social media, academic publications, patents, transportation, and culture. In addition, we will discuss connections with disciplines including economics, sociology, history, psychology, and information science. While this course does not cover the entire scope of computational social science, which spans a wide range of topics, it aims to provide a broad introduction centered on fundamental and versatile concepts.

(計算社会科学とは社会現象を計算科学的に解明するアプローチです。近年の大規模なデータが蓄積やそれに伴う数理的な理論な発展が、多様な個人のインタラクションにより生じる社会現象の理解や予測を可能にしつつあります。講義では、集団現象一般に見られる統計的性質、複雑ネットワーク解析を始めとするデータ解析、統計モデリング、シミュレーションなどの基礎的理論に重点を起きつつ、SNS、論文、特許、交通、文化などの大規模なデータ解析の最新の研究を紹介します。また、経済学/社会学/歴史学/心理学/情報学などの学問との接続を議論していきます。本授業は多岐に渡る計算社会科学のスコープを網羅するわけではありませんが、基礎的かつ汎用的な概念を中心に幅広く紹介します。)