  Cybersecurity analysts work on large communication data sets to perform
investigative analysis by painstakingly going over thousands of email
conversations to find potential scamming activities and the network of cyber
scammers. Traditionally,experts used email clients, database systems and text
editors to perform this investigation. With the advent of technology,elaborate
tools that summarize data more efficiently by using cutting edge data
visualization techniques have come out. Beagle[1] is one such tool which
visualizes the large communication data using different panels such that the
inspector has better chances of finding the scam network. This paper is a
report 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 more
visualizations that we feel would help in grouping and analyzing the e-mail
data more efficiently. Lastly, we have also presented a case study that shows
the potential use of our tool in a real-world scenario.
