The Computational Social Science Capstone Project is an integrative lab where learners apply multi-method workflows of computational social science. The course equips participants with skills in webscraping, social network analysis, natural language processing, and agent-based computer simulations. Through this capstone project, learners explore the new frontier of social science in the digital age.
This comprehensive course enables learners to understand and apply computational social science methodologies, fostering a new generation of computational social scientists.
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The course consists of four modules covering webscraping, social network analysis, natural language processing, and agent-based computer simulations, preparing learners to execute comprehensive multi-method workflows in computational social science.
Learners will explore webscraping techniques to collect data from social media platforms, building on the skills obtained in the previous courses. They will engage in an integrative lab to apply their knowledge and address questions raised by peers.
In this module, participants will delve into social network analysis, learning how to analyze and visualize resulting networks. They will then apply these skills in an integrative lab and engage in discussions with peers to deepen their understanding.
Participants will utilize machine learning-powered natural language processing to analyze key aspects of the collected data. They will engage in an integrative lab to apply their skills and discuss their findings with peers.
Learners will explore agent-based computer simulations to scrutinize aspects of society and explore generative mechanisms. They will participate in an integrative lab and engage in discussions to enhance their understanding.
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