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Computational Social Science

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Using data science to understand changes in human interactions

About CSS

The Center supports research in the overlapping areas of the social sciences and computer science.

The field of computational social science exists because advances in technology have generated an unprecedented volume of digital data that can be used to research traditional social science topics like democracy, security, economic growth, and inequality. Computational methods include:

  • Data mining
  • Natural language processing
  • Text analysis
  • Web scraping
  • Data visualization
  • Machine learning

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Recent News

Stanford IRiSS is home to one of approximately 30 Federal Statistical Research Data Centers (FSRDCs) scattered across the country. Since 2010, IRiSS has hosted the Stanford FSRDC at its 30 Alta Road office.
Data science is a large and expanding field, and the issues it confronts vary greatly with each domain of application. To understand issues within each applied domain, one cannot simply read a book on education theory to comprehend it. Therefore, it is important to have a rich immersion and dialogue with the empirical domain.
One of IRiSS's mandates is to facilitate computationally intensive social science research. IRiSS sponsors a number of trainings and workshops to this end, but a major priority is funding research itself.

CSS Fellowships

2019-20 CSS Fellows

The IRiSS Center for Computational Social Science runs a competitive grant proposal program that awards five Computational Social Science Fellowships per year. The funding assists graduate students conducting computational research to acquire data, pay RAs to process and validate data, and other research activities.

The 2019-2020 CSS Fellows conducted innovate computational research that pushed disciplinary boundaries and yielded a trove of rich insights. The research reports provided by the fellows describe their groundbreaking findings and the impact of the fellowships on their research. Read the 2019-2020 research reports.