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
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Joseph, Minumol, "Speaker Identification in Live Events using Twitter" (2015). Computer Science and Engineering Theses. 509.
https://mavmatrix.uta.edu/cse_theses/509
Comments
Degree granted by The University of Texas at Arlington