Lisa Singh and Collaborators Receive a Large NSF Grant to Explore the Future of Quantitative Research in the Social Sciences

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Prof. Lisa Singh in Computer Science and her collaborators at Georgetown University and University of Michigan-Ann Arbor have received a new grant from the National Science Foundation.

In order to extract significant research value from new forms of organic data, computer scientists and social scientists must integrate their expertise – or converge – to create and adapt computer science algorithms and data mining methods in ways that adhere to the design structures, measurement rigor and ethical protections of social science. The project team, representing the breadth of behavioral/social science and computer science, proposes accomplishing this by cross-pollinating ideas from different disciplines about data acquisition, sampling, design, data transformation, validity, reliability, modeling and ethics to establish new methods and guidelines for leveraging social media data to answer questions about human opinion and behavior.

Specifically, this project will (1) develop a detailed, hybrid methodology (Iterative Method for Social Media Research  – IMSMR) that integrates relevant components of existing social science methodologies with relevant components of the knowledge discovery process to enhance research practices in both social and computer science fields; (2) use IMSMR to establish guidelines for using an array of different social media data to answer questions across different social and data science disciplines; (3) test and refine the methodology and guidelines on different research exemplars that spans multiple SBE (Social, Behavioral, and Economic) disciplines; and (4) develop a shared text analytic research portal that enables social scientists to generate structured variables using state of the art natural language processing and data mining that adhere to the validity and reliability standards of social science.