Food for Thought

Presenters

Disciplines

Artificial Intelligence and Robotics | Graphics and Human Computer Interfaces | Other Computer Sciences

Abstract (300 words maximum)

This project explores public opinion on the Supplemental Nutrition Assistance Program (SNAP) in news and social media outlets, and tracks elected representatives’ voting records on issues relating to SNAP and food insecurity. We used machine learning, sentiment analysis, and text mining to analyze national and state level coverage of SNAP in order to gauge perceptions of the program over time across these outlets. Preliminary results indicate that the majority of news coverage is negative, more partisan news outlets have more extreme sentiment, and that clustering of negative reporting on SNAP occurs the South. Our final results and tools will be displayed in an on-line application that the ACFB Advocacy team can use to inform their communication to relevant stakeholders.

Primary Investigator (PI) Name

Carl DiSalvo

Additional Faculty

n/a

This document is currently not available here.

Share

COinS
 

Food for Thought

This project explores public opinion on the Supplemental Nutrition Assistance Program (SNAP) in news and social media outlets, and tracks elected representatives’ voting records on issues relating to SNAP and food insecurity. We used machine learning, sentiment analysis, and text mining to analyze national and state level coverage of SNAP in order to gauge perceptions of the program over time across these outlets. Preliminary results indicate that the majority of news coverage is negative, more partisan news outlets have more extreme sentiment, and that clustering of negative reporting on SNAP occurs the South. Our final results and tools will be displayed in an on-line application that the ACFB Advocacy team can use to inform their communication to relevant stakeholders.