Date of Graduation
5-2021
Document Type
Thesis
Degree Name
Bachelor of Science
Degree Level
Undergraduate
Department
Computer Science and Computer Engineering
Advisor/Mentor
Gauch, Susan
Committee Member/Reader
Gauch, Susan
Committee Member/Second Reader
Nelson, Alexander
Committee Member/Third Reader
Le, Thi Hoang Ngan
Abstract
The purpose of this project is to explore the effectiveness of emotional analysis as a means to automatically moderate content or flag content for manual moderation in order to reduce the workload of human moderators in moderating toxic content online. In this context, toxic content is defined as content that features excessive negativity, rudeness, or malice. This often features offensive language or slurs. The work involved in this project included creating a simple website that imitates a social media or forum with a feed of user submitted text posts, implementing an emotional analysis algorithm from a word emotions dataset, designing a system to configure tolerance thresholds on a per-emotion basis, implementing the process of determining violations of incoming text posts using the configuration, and testing the effectiveness of the emotional analysis algorithm at determining toxic posts using a dataset of posts that have been manually reviewed for toxicity by a group of human moderators.
Keywords
software; moderation; moderator; emotional analysis; sentiment analysis
Citation
Shelnutt, J. (2021). Applying Emotional Analysis for Automated Content Moderation. Computer Science and Computer Engineering Undergraduate Honors Theses Retrieved from https://scholarworks.uark.edu/csceuht/93
Included in
Analysis Commons, Applied Statistics Commons, Other Computer Sciences Commons, Software Engineering Commons