Negotiating Formal Schooling, Multiple Identities, and Community Advocacy: (Counter)-Narratives of Somali Bantu Refugees in the United States

Negotiating Formal Schooling, Multiple Identities, and Community Advocacy: (Counter)-Narratives of the Somali Bantu Refugees in the United States examines the educational experiences of Somali-Bantu refugees resettled in Upstate, New York. It explores how they negotiate their multiple identities - race, gender, class, religion, culture, language, accent, and immigrant status -within the formal school setting and environment. Additionally, it highlights the role of the Somali Bantu community organizations in advocating and implementing resettlement services and academic resources for their people. Using critical race theory as theoretical lens and methodology, a qualitative research was conducted to collect data from nine Somali Bantu participants. The findings suggest that the participants experienced both successes and challenges while negotiating formal schooling. Their multiple identities subjected them to bias and discrimination within the schools and the society. Nonetheless, the community organizations play a significant role in supporting their children’s academic achievement as well as sustaining their cultural values and language. Based on the findings, the study recommends strategies and reforms that are conducive for equity in education, academic achievement, and cultural tolerance for a successful transition and integration of the Somali Bantus and other refugees in the United States

Exploring Cyberterrorism, Topic Models and Social Networks of Jihadists Dark Web Forums: A Computational Social Science Approach

This three-article dissertation focuses on cyber-related topics on terrorist groups, specifically Jihadists’ use of technology, the application of natural language processing, and social networks in analyzing text data derived from terrorists\u27 Dark Web forums. The first article explores cybercrime and cyberterrorism. As technology progresses, it facilitates new forms of behavior, including tech-related crimes known as cybercrime and cyberterrorism. In this article, I provide an analysis of the problems of cybercrime and cyberterrorism within the field of criminology by reviewing existing literature focusing on (a) the issues in defining terrorism, cybercrime, and cyberterrorism, (b) ways that cybercriminals commit a crime in cyberspace, and (c) ways that cyberterrorists attack critical infrastructure, including computer systems, data, websites, and servers. The second article is a methodological study examining the application of natural language processing computational techniques, specifically latent Dirichlet allocation (LDA) topic models and topic network analysis of text data. I demonstrate the potential of topic models by inductively analyzing large-scale textual data of Jihadist groups and supporters from three Dark Web forums to uncover underlying topics. The Dark Web forums are dedicated to Islam and the Islamic world discussions. Some members of these forums sympathize with and support terrorist organizations. Results indicate that topic modeling can be applied to analyze text data automatically; the most prevalent topic in all forums was religion. Forum members also discussed terrorism and terrorist attacks, supporting the Mujahideen fighters. A few of the discussions were related to relationships and marriages, advice, seeking help, health, food, selling electronics, and identity cards. LDA topic modeling is significant for finding topics from larger corpora such as the Dark Web forums. Implications for counterterrorism include the use of topic modeling in real-time classification and removal of online terrorist content and the monitoring of religious forums, as terrorist groups use religion to justify their goals and recruit in such forums for supporters. The third article builds on the second article, exploring the network structures of terrorist groups on the Dark Web forums. The two Dark Web forums\u27 interaction networks were created, and network properties were measured using social network analysis. A member is considered connected and interacting with other forum members when they post in the same threads forming an interaction network. Results reveal that the network structure is decentralized, sparse, and divided based on topics (religion, terrorism, current events, and relationships) and the members\u27 interests in participating in the threads. As participation in forums is an active process, users tend to select platforms most compatible with their views, forming a subgroup or community. However, some members are essential and influential in the information and resources flow within the networks. The key members frequently posted about religion, terrorism, and relationships in multiple threads. Identifying key members is significant for counterterrorism, as mapping network structures and key users are essential for removing and destabilizing terrorist networks. Taken together, this dissertation applies a computational social science approach to the analysis of cyberterrorism and the use of Dark Web forums by jihadists