ORCID Identifier(s)

0000-0002-4560-8840

Graduation Semester and Year

2015

Language

English

Document Type

Thesis

Degree Name

Master of Science in Computer Science

Department

Computer Science and Engineering

First Advisor

Chengkai Li

Abstract

The prevalence of social media has given rise to a new research area. Data from social media is now being used in research to gather deeper insights into many different fields. Twitter is one of the most popular microblogging websites. Users express themselves on a variety of different topics in 140 characters or less. Oftentimes, users “tweet” about issues and subjects that are gaining in popularity, a great example being politics. Any development in politics frequently results in a tweet of some form. The research which follows focuses on identifying a speaker’s name at a live event by collecting and using data from Twitter. The process for identification involves collecting the transcript of the broadcasting event, preprocessing the data, and then using that to collect the necessary data from Twitter. As this process is followed, a speaker can be successfully identified at a live event. For the experiments, the 2016 presidential candidate debates have been used. In principle, the thesis can be applied to identify speakers at other types of live events.

Keywords

Data mining, Text processing, Twitter

Disciplines

Computer Sciences | Physical Sciences and Mathematics

Comments

Degree granted by The University of Texas at Arlington

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