Jiayi Zhang
Pronouns: She/her/hers
Research Mentor(s): Lu Wang
Co-Presenter: Peterson, Margaret
Research Mentor School/College/Department: Computer Science and Engineering / Engineering
Presentation Date: April 20
Presentation Type: Poster
Session: Session 6 – 4:40pm – 5:30 pm
Room: League Ballroom
Authors: Jiayi Zhang, Margaret Peterson, Isabella Allada, Frederick Zhang, Lu Wang
Presenter: 76
Abstract
Media sources in the United States often contain bias and contribute heavily to America’s polarized political landscape. This project aims to build computational systems to detect and quantify how media ideology affects the creation and presentation of news at the level of articles and their constituent events. This project will promote the transparency of news production and enhance public awareness of media decisions. Because the natural language processing model for this project requires a vast batch of training datasets, five students from a diverse array of backgrounds are involved in annotating and collecting data for these political news articles with bias. The news articles were grouped into triplets based on the topic of the article. The student’s annotations consisted of detecting the entities, marking sentiments between entities, the author’s sentiment towards all entities, the political affiliation of those entities, and the article’s ideology. The developed datasets and methods can effectively and efficiently support the measurement of media ideology at organization- and article-levels, which facilitates research in broad areas, including political science, social science, and communications.
Engineering
