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Dissertation/Thesis Abstract
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Extremism, for centuries, have existed in virtually every culture. With the advancement of communication and technology in the past few decades, extremism was able to spread more easily across the country through connections and networking. In this study, we will look closely into simulated connections of extremist groups and use different methods to analyze these networks. Social Network Analysis will be introduced, followed by the use of Exponential Random Graph, Nearest-Neighbor and Auto-Logistic to model the data.
| Advisor: | Korosteleva, Olga |
| Commitee: | Suaray, Kagba, Safer, Alan |
| School: | California State University, Long Beach |
| Department: | Mathematics and Statistics |
| School Location: | United States -- California |
| Source: | MAI 82/2(E), Masters Abstracts International |
| Source Type: | DISSERTATION |
| Subjects: | Statistics, Applied Mathematics, Web Studies |
| Keywords: | R Language, Social Network Analysis, Social Networks |
| Publication Number: | 27829907 |
| ISBN: | 9798664724585 |
