Date of Award

2025

Document Type

Honors

Degree Name

General Beadle Honors Program

Department

Computer Science

Abstract

In the modern cyberscape, phishing serves as a useful means for attackers to gain access to their victims. Creating the best phishing message is a sophisticated art form, with one common tactic involving asking the victim to follow through on an action with great haste. Through the utilization of sentiment analysis, or weighing how much of a certain emotion is conveyed in text form, classifying this sense of urgency becomes relatively trivial. The research done in this project attempts to create a working machine learning model that can categorize the urgency value of a body of text. The data gathered from the model is used to visualize how urgent large data sets can be, and potentially can be used to determine the connection between phishing likelihood and urgency scores.

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