Project Director

Tanis, Craig

Department Examiner

McCullough, Claire; Dumas, Joe

Department

Dept. of Computer Science and Engineering

Publisher

University of Tennessee at Chattanooga

Place of Publication

Chattanooga (Tenn.)

Abstract

Given a set of text with known authors, is it possible to take new text, not knowing who wrote it, and correctly identify the author? One way to do this is to analyze the text using Markov chains. This research project will first attempt to answer this question using books available in the public domain. Using what is learned from trying to identify authors of books, the primary goal of this project is to identify the best way to guess the author of a post on the social media network Twitter using Markov chains.

Acknowledgments

Acknowledgements go to my thesis director, Dr. Craig Tanis, and to the other members of my examination committee, Dr. Claire McCullough and Dr. Joe Dumas.

Degree

B. S.; An honors thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Bachelor of Science.

Date

12-2017

Subject

Markov processes; Twitter

Keyword

Twitter; Language analysis; Markov chain; Lisp; Python; Writer identification

Discipline

Computer Sciences

Document Type

Theses

Extent

47 leaves

DCMI Type

Text

Language

English

Rights

http://rightsstatements.org/vocab/InC/1.0/

License

http://creativecommons.org/licenses/by-nc-sa/3.0/

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