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Thesis-final-v2.3.pdf (897.07 KB)

ETD Abstract Container

Abstract Header

Content-based Clustering and Visualization of Social Media Text Messages

Barnard, Sydney A.
http://rave.ohiolink.edu/etdc/view?acc_num=wright1527085083542772

Abstract Details

2018, Master of Science (MS), Wright State University, Computer Science.
Although Twitter has been around for more than ten years, crisis management agencies and first response personnel are not able to fully use the information this type of data provides during a crisis or natural disaster. This thesis addresses clustering and visualizing social media data by textual similarity, rather than by only time and location, as a tool for first responders. This thesis presents a tool that automatically clusters geotagged text data based on their content and displays the clusters and their locations on the map. It allows at-a-glance information to be displayed throughout the evolution of a crisis. For accurate clustering, we used silhouette coefficients to determine the number of clusters automatically. To visualize the topics (i.e., frequent words) within each cluster, we used the word cloud. This tool could be easily used by first response and official management personnel to quickly determine when a crisis is occurring, where it is concentrated, and what resources to best deploy to stabilize the situation.
Soon Chung, Ph.D. (Advisor)
Nikolaos Bourbakis, Ph.D. (Committee Member)
Vincent Schmidt, Ph.D. (Committee Member)
37 p.
Computer Science
Twitter; content-based clustering; social media; crisis management

Recommended Citations

Citations

  • Barnard, S. A. (2018). Content-based Clustering and Visualization of Social Media Text Messages [Master's thesis, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1527085083542772

    APA Style (7th edition)

  • Barnard, Sydney. Content-based Clustering and Visualization of Social Media Text Messages. 2018. Wright State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright1527085083542772.

    MLA Style (8th edition)

  • Barnard, Sydney. "Content-based Clustering and Visualization of Social Media Text Messages." Master's thesis, Wright State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=wright1527085083542772

    Chicago Manual of Style (17th edition)

wright1527085083542772
742
© 2018, all rights reserved.
This open access ETD is published by Wright State University and OhioLINK.