In order to investigate and comprehend human behavior in the digital age, computational social science is an interdisciplinary field that blends social science ideas and methodologies with computing approaches.

Social media data, online communication data, sensor data, and other digital footprints produced by individuals and groups are only a few of the data types used in computational social science.

In order to study and simulate social phenomena, computational social science uses techniques including network analysis, machine learning, natural language processing, agent-based modeling, and data visualization.

Utilizing computational tools and methodologies, computational social science analyzes massive amounts of social data to find patterns and insights that may not be visible using only traditional approaches.

Social network analysis, opinion mining, sentiment analysis, social impact modeling, political forecasting, and urban planning are just a few of the many fields where computational social science has applications.