Isabella Allada
Pronouns: she/her
Research Mentor(s): Lu Wang
Co-Presenter: Peterson, Maggie
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: Maggie Peterson, Jiayi Zhang
Presenter: 75
Abstract
News articles are the main source where people consume information, but oftentimes the news contains partisan bias that can color how people perceive certain events. This project aims to detect and quantify political bias in news articles in order to bring awareness to media bias and transparency to news production. Using extractive natural language processing, we will design a framework to detect media bias. Extractive natural language processing involves using the raw text from the article to inform the machine learning algorithms of patterns of bias. Our protocol for measuring bias involves analyzing the relationship between and the political ideologies of political entities in each article, as well as identifying the political ideology of the news source.
Engineering
