Document Type
Thesis
First Faculty Advisor
Thomas Dougherty
Second Faculty Advisor
Amy Crouch
Keywords
cancel culture; Twitter; data analysis; sentiment analysis; topic analysis
Publisher
Bryant University
Rights Management
CC-BY-NC-ND
Abstract
This paper utilizes Data Science and Applied Statistic techniques, to perform an analytical dive into Cancel Culture as it is referenced and used on Twitter. The research focuses on analyzing how Cancel Culture has affected the sentiment of Twitter, specifically how it impacts prominent topics in the media that have occurred between February 2021 to September 2021. The development of a topic and sentiment analysis will be based on 1,302,844 Tweets collected using Twitter’s API. Cancel Culture became popularized on social media in the past few years and there is little concrete information regarding its process and the demographics it encapsulates. The primary goal of my analysis is to give insight to Cancel Culture’s workings and why it is so prevalent in today's day and age on social media.
Included in
Databases and Information Systems Commons, Data Science Commons, Other Computer Sciences Commons
