Graduation Year

2017

Date of Submission

4-2017

Document Type

Campus Only Senior Thesis

Degree Name

Bachelor of Arts

Department

Computer Science

Reader 1

Blake Hunter

Reader 2

Lisa Kaczmarczyk

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Terms of Use for work posted in Scholarship@Claremont.

Rights Information

© 2017 Wyatt J Cooper

Abstract

This paper explores topic modeling via unsupervised non-negative matrix factorization. This technique is used on a variety of sources in order to extract salient topics. From these topics, hidden entity networks are discovered and visualized in a graph representation. In addition, other visualization techniques such as examining the time series of a topic and examining the top words of a topic are used for evaluation and analysis. There is a large software component to this project, and so this paper will also focus on the design decisions that were made in order to make the program developed as versatile and extensible as possible.

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