Faculty Advisor

Kay Graves

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Student Status

Undergraduate

Major

Applied Mathematics

Publication Date

Spring 2021

Presentation Type

Slideshow Presentation

Department

Mathematics and Computer Science

Degree Program

Data Analysis and Communication

Description

This project focuses on mathematical applications for one-on-one texting conversations. Welcome to the realm of conversational A.I. (artificial intelligence), a field that also studies the commonly-known predictive text. Instead of suggesting words, however, this project will make predictions in text sentiment. Text sentiment models detect emotion in natural written language. With the development of models that can tag present emotions, this project looks to further apply the field of text sentiment. If a model exists to tag present emotion, then perhaps the tags can be used to predict future emotion. This project specifically applies this question to texting conversations between two people and tries to predict the emotion of a text message response before it has occurred. The goal is for a sender to have more insight into response sentiment before choosing to send a message. The resulting predictions are built upon concepts in logistic regression, and the code will be written in Python using Jupyter Notebook.

Creative Commons License

Creative Commons Attribution-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-No Derivative Works 4.0 License.

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