Date of Graduation
7-2021
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Computer Science (PhD)
Degree Level
Graduate
Department
Computer Science & Computer Engineering
Advisor/Mentor
Liu, Xiaoqing "Frank"
Committee Member
Zhan, Justin
Second Committee Member
Li, Qinghua
Third Committee Member
Panda, Brajendra N.
Fourth Committee Member
Adams, Douglas J.
Keywords
argument discovery; argument search; contoversy; cyber-argumentation; focal set; mobile app
Abstract
User-generated content (UGC) platforms host different forms of information, such as audio, video, pictures, and text. They have many online applications, such as social media, blogs, photo and video sharing, customer reviews, debate, and deliberation platforms. Usually, the content of these platforms is provided and consumed by users. Most of these platforms, mainly social media and blogs, are often used for online discussion. These platforms offer tools for users to share and express opinions. Commonly, people from different backgrounds and origins discuss opinions about various issues over the Internet. Furthermore, discussions among users contain substantial information from which knowledge about collective intelligence can be extracted. Collective Intelligence is wisdom and knowledge that grows when a group works together collectively or cooperatively. In this dissertation, strides in the cyber-argumentation field are made. The body of this work in this dissertation revolves around different areas: (1) bringing the intelligent cyber-argumentation into the handheld device space and showing the effectiveness of bringing large-scale cyber-argumentation into handheld devices, (2) constructing the argument discovery framework and identifying the arguments attributes, (3) modeling the controversial degree of cyber-argumentation discussions using well-known measures and, (4) discovering topic-oriented focal sets in cyber-argumentation using link analysis, topic modeling and social roles. This dissertation is concluded by discussing the challenging technical implications of this emerging research area and proposing future work avenues.
Citation
Althuniyan, N. (2021). Towards a Large-Scale Intelligent Mobile-Argumentation and Discovering Arguments, Controversial Topics and Topic-Oriented Focal Sets in Cyber-Argumentation. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/4132
Included in
Graphics and Human Computer Interfaces Commons, Mass Communication Commons, Programming Languages and Compilers Commons, Social Media Commons, Software Engineering Commons