Author ORCID Identifier
Semester
Spring
Date of Graduation
2023
Document Type
Thesis
Degree Type
MS
College
Statler College of Engineering and Mineral Resources
Department
Lane Department of Computer Science and Electrical Engineering
Committee Chair
Xin Li
Committee Member
Brian Woerner
Committee Member
Omid Dehzangi
Abstract
This thesis focuses on the pressing issue of illicit drug trafficking and its impact on public health and safety at a global level. With the advent of digital technologies and social media platforms, combating drug trafficking has become increasingly challenging for law enforcement and researchers alike. Among these platforms, Instagram, a popular photo and video-sharing social networking platform, has emerged as a prominent hub for drug trafficking activities.
In this study, we delve into the effectiveness of community and key player detection algorithms in identifying and disrupting illicit drug supply networks on Instagram. To conduct our research, we collected real Instagram data spanning from June to August 2022. We examined several community detection algorithms, including Louvain, Newman-Girvan, Infomap, Label Propagation, and Hierarchical Clustering. Additionally, we explored key player algorithms, namely CDKPE, TopRank, K-core, and KPEI, the latter being a novel algorithm introduced in this study. Our objective was to assess the performance of these algorithms in accurately identifying and targeting drug trafficking networks.
Our findings reveal that the Louvain and Newman-Girvan algorithms outperformed others in terms of community detection, demonstrating their effectiveness in identifying cohesive groups involved in drug trafficking on Instagram. In terms of key player detection, the CDKPE and KPEI algorithms emerged as the most effective, highlighting the individuals who play pivotal roles within these networks.
These algorithms offer practical applications for law enforcement agencies seeking to disrupt drug trafficking operations on Instagram. By emphasizing the importance of leveraging advanced analytical tools, our study underscores the significance of combating drug trafficking on social media platforms.
Recommended Citation
Niamke Aman, Akassi Rachel, "Community and key player detection for disrupting illicit drug supply networks in social media platforms – especially on Instagram" (2023). Graduate Theses, Dissertations, and Problem Reports. 11739.
https://researchrepository.wvu.edu/etd/11739