Historical Big Data Analysis to Study the Evolution of Juvenile Delinquency in the United States
A multidisciplinary project that studied juvenile delinquency as a social construction using historical newspaper data from the United States. The project was funded by the National Science Foundation (NSF) through Extreme Science and Engineering Discovery Environment (XSEDE) under the grant number ACI-1548562.
Principal Investigator: Yu Zhang, Ph.D., Assistant Professor, Department of Criminology, California State University, Fresno
Role: Research Software Engineer
Responsibilities
- Collaborate with the project team to define the project scope, goals, and deliverables.
- Design and develop software for analyzing newspaper data from the Library of Congress Chronicling America Collection.
- Develop newspaper article segmentation software using deep learning techniques (Mask R-CNN).
Related Publications
Toward a Big Data Analysis System for Historical Newspaper Collections Research
Sandeep Puthanveetil Satheesan, Bhavya, Adam Davies, Alan B. Craig, Yu Zhang, ChengXiang Zhai, "Toward a Big Data Analysis System for Historical Newspaper Collections Research." Proceedings of the Platform for Advanced Scientific Computing Conference, 2022.
A Historical Big Data Analysis to Understand the Social Construction of Juvenile Delinquency in the United States
Sandeep Puthanveetil Satheesan, Alan B Craig, Yu Zhang, "A Historical Big Data Analysis to Understand the Social Construction of Juvenile Delinquency in the United States." 2019 15th International Conference on eScience (eScience), 2019.