Analyzing 2020 Protest Effects Using Datasets to Visualize Change

Amrutha Ragothaman, Aspen Akunne, Eric Laundevede, and Drs. Jean Chu, Daehan Kwak School of Computer Science and Technology, Kean University, Union, NJ 07083

Since May 2020, the George Floyd protests have caused nationwide unrest. According to the ACLED, 93% of BLM adjacent protests were peaceful. But, 42% of public poll respondents believed the opposite. This contrast displays an issue between the perception regarding the content shown about protests. The media itself focuses mainly on the internal effects involving property damage or the large masses of people. But, from the poll referenced above it can be seen that this can skew public perception of protests. There exists a severe dearth of data gathered or analyzed involving legislation. The public is mostly pushed to ignore the long term effects of protests even past the original event. 

This research seeks to close that gap by web scraping for headlines to examine the sentiments that can change legislature. The changing opinions of the public and government officials will also be examined through Twitter to gain a better picture of the effects of protests. Using supplemental data from protest tracking organizations, certain high protest areas will be examined for the effects. The main goal for this project in the end is to be able to visualize this data to be able to draw a conclusion about protests and legislative change using a data mapping program. 

Additional Abstract Information

Presenters: Amrutha Ragothaman, Aspen Akunne, Eric Landaverde

Institution: Kean University

Type: Poster

Subject: Computer Science

Status: Approved

Time and Location

Session: Poster 5
Date/Time: Tue 12:30pm-1:30pm
Session Number: 4019