Understanding and De-biasing User Media Consumption
Project Description
This project aims to develop a scalable method to jointly measure media bias and public opinion on social/economic/political issues. It relies on a revealed preference approach that utilizes online news consumers’ responses to articles or social media posts. We will conduct online experiments with recruited users to gather their (1) passive behavioral metrics, covering which media pieces each user reads and how their attention varies within each media piece and across different pieces; (2) active private behavioral metrics, inviting users to annotate each media piece and give a media bias rating to it. The output will be a first-of-its-kind dataset that covers how users with differing backgrounds react to media pieces.
Supervisor
LU, Yang
Co-Supervisor
HAGMANN, David
Quota
5
Course type
UROP1000
UROP1100
UROP2100
UROP3100
UROP4100
Applicant's Roles
The students are expected to help with the following tasks related to the online experiments
1) curate news articles on various economic and political issues
2) test the web portal and browser plugin that will be used in the experiments
3) conduct and monitor the online experiments
4) process and analyze the data gathered from the experiments
1) curate news articles on various economic and political issues
2) test the web portal and browser plugin that will be used in the experiments
3) conduct and monitor the online experiments
4) process and analyze the data gathered from the experiments
Applicant's Learning Objectives
1) to gain hands-on experience of designing and conducting online experiments
2) to acquire practical skills of data analytics
3) to gain exposure to the frontier of the literature on behavioral economics and media bias
2) to acquire practical skills of data analytics
3) to gain exposure to the frontier of the literature on behavioral economics and media bias
Complexity of the project
Challenging