CrimeSeen: An Interactive Visualization Environment for Scenario Testing on Criminal Cocaine Networks
| Authors |
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| Publication date | 2024 |
| Host editors |
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| Book title | Computational Science – ICCS 2024 |
| Book subtitle | 24th International Conference, Malaga, Spain, July 2–4, 2024 : proceedings |
| ISBN |
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| ISBN (electronic) |
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| Series | Lecture Notes in Computer Science |
| Event | 24th International Conference on Computational Science, ICCS 2024 |
| Volume | Issue number | III |
| Pages (from-to) | 195-204 |
| Number of pages | 10 |
| Publisher | Cham: Springer |
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| Abstract |
The resiliency of criminal networks against law enforcement interventions has driven researchers to investigate methods of creating accurate simulated criminal networks. Despite these efforts, insights reaching law enforcement agencies remain general and insufficient, warranting a new approach. Therefore, we created CrimeSeen - an interactive visualization and simulation environment for exploring criminal network dynamics using computational models. CrimeSeen empowers law enforcement agencies with the possibility to independently test specific scenarios and identify the most effective disruption strategy before deploying it. CrimeSeen comprises of three components: Citadel, a web-based network visualization and simulation tool serving as the interface; the model, defining rules for criminal network dynamics over time, with the Criminal Cocaine Replacement Model as the use-case in this project; and the simulator, connecting the model and interface and enhancing their functionality through transformations, triggers, and statistics. CrimeSeen was evaluated with sequential usability testing, revealing a positive trend in effectiveness and efficiency over time, with mean scores exceeding 80%. However, user satisfaction did not significantly change and remained below the average for web applications, prompting recommendations for future work. |
| Document type | Conference contribution |
| Note | With supplemental material |
| Language | English |
| Published at | https://doi.org/10.1007/978-3-031-63759-9_24 |
| Other links | https://www.scopus.com/pages/publications/85199649419 |
| Downloads |
978-3-031-63759-9_24
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