Excerpt from course description

Computational Social Science: People and Organizations in the Digital Age

Introduction

Please note that this is a preliminary course description. The final version will be published in June 2027.

In 2024, the world produced an astounding 150 zettabytes of data—on WhatsApp alone, we send 100 billion messages every day. It would take hundreds of millions of years just to download all the information currently available online. We are living in an unprecedented explosion of digital data. This data revolution offers social scientists and organizations an extraordinary opportunity to gain deeper, more precise insights into human behaviour, society, and organizations. The rapidly growing field of Computational Social Science (CSS) takes up this challenge by utilizing novel data sources, massive datasets, and cutting-edge technologies—such as social network analysis, machine learning, and artificial intelligence—to reveal powerful insights about people and organizations. Mastering these methods will equip you with in-demand, career-ready skills that set you apart in data-driven workplaces across research, policy, and industry.

In this course, you’ll learn how recent computational advances can help tackle urgent societal challenges, boost operational efficiency, and enable data-driven decisions. You will learn how large language models can provide actionable insights from social, political, and organizational texts; how network analysis maps organizational structures and reveals hidden collaboration patterns; and how predictive modeling forecasts everything from macro-economic trends to key organizational performance metrics. Along the way, you’ll gain insights into how data-centric methods can advance sustainability goals and grapple with the ethical questions that accompany the digital revolution.

Through a series of hands-on tutorials, you’ll gain practical, career-ready skills—including how to collect data through APIs and web scraping, analyse social networks, access and prompt-engineer large language models, and apply machine learning techniques. These tutorials aim to place you at the forefront of the digital revolution, equipping you with cutting-edge skills to decode human behaviour, drive organizational change, and tackle complex challenges facing today’s institutions. Whether you’re aiming for a career in research, human resources, consulting, organizational development, talent recruitment, or change management, this course will help set you apart from other graduates by giving you the digital knowledge and tools to thrive in a data-driven world.

Prerequisite: No prior coding or data science experience is required. Whether you are tech-savvy or completely new to computational methods, this course will provide you with valuable, future-oriented skills and knowledge to help you stand out professionally.

Course content

This course explores key topics at the intersection of social science, technology, and organizational behaviour, including:          

  • The rapidly growing field of CSS and how it can inform the structure and dynamics of social systems.
  • Emerging data sources in organizational settings, including geo-location, sensor data, and digital traces.
  • How modern computational tools—such as social network analysis, natural language processing, and artificial intelligence—can be used to improve organizations and solve societal problems.
  • The social cognitive processes active in organizations, such as social contagion and the wisdom of crowds.
  • Ethical challenges surrounding data use and privacy in organizations and society at large.

Disclaimer

This is an excerpt from the complete course description for the course. If you are an active student at BI, you can find the complete course descriptions with information on eg. learning goals, learning process, curriculum and exam at portal.bi.no. We reserve the right to make changes to this description.