Introduction

This introductory chapter discusses the integration of computational social science (CSS) with sociology. CSS, comprising agent-based modeling and big data analysis, has revolutionized social scientific studies. Agent-based modeling enables the simulation of complex social phenomena by allowing virtual agents to interact within varied environments. This method facilitates the exploration of micro-macro linkages in social phenomena. Big data analysis, the second pillar of CSS, differs from traditional surveys by utilizing readily available digital data. This approach offers advantages in terms of scale, continuous data collection, and nonreactivity of digital data. We note, however, that CSS often neglects the crucial aspects of meaning and interpretation in human behavior, which have been central to sociology since its inception. We argue that incorporating these elements into CSS can significantly enhance its analytical power and relevance to sociological inquiry. The purpose of the book is to explore the potential collaboration between CSS and sociology to advance both fields. Each chapter shares this objective from various perspectives, focusing on how CSS can address core sociological questions and contribute to theoretical development in sociology. The book aims to bridge the gap between computational techniques and sociological theory, advocating for a synergy that enriches both disciplines.