Date of Award
6-9-2022
Document Type
Thesis
Publisher
Santa Clara : Santa Clara University, 2022.
Department
Computer Science and Engineering
First Advisor
Yi Fang
Abstract
News is a constant part of our lives, and has a significant impact on how we see the world. Simply put, journalistic sources are not diverse enough, and typically are only those in the majority. Newsrooms have made passionate declarations about wanting more diversity in their news sources. Our project aims to help with that. Building on top of the DEI toolkit, we aim to help newsrooms increase the diversity of their sources by analyzing their sources using a google search to pick an image and facial recognition software to determine the gender and race of the image.
Recommended Citation
Johnson, Austin; Mercado, Carlos; and Khan, Sabiq, "Improving Diversity in Journalistic Sources with Computer Vision" (2022). Computer Science and Engineering Senior Theses. 229.
https://scholarcommons.scu.edu/cseng_senior/229