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Cybersecurity analysts work on large communication data sets to performinvestigative analysis by painstakingly going over thousands of emailconversations to find potential scamming activities and the network of cyberscammers. Traditionally,experts used email clients, database systems and texteditors to perform this investigation. With the advent of technology,elaboratetools that summarize data more efficiently by using cutting edge datavisualization techniques have come out. Beagle[1] is one such tool whichvisualizes the large communication data using different panels such that theinspector has better chances of finding the scam network. This paper is areport on our work to implement and improve the work done by Jay Koven et al.[1]. We have proposed and demonstrated via implementation, a few morevisualizations that we feel would help in grouping and analyzing the e-maildata more efficiently. Lastly, we have also presented a case study that showsthe potential use of our tool in a real-world scenario.

Lessons Learned Developing and Extending a Visual Analytics Solution for Investigative Analysis of Scamming Activities