DocumentCode :
3717274
Title :
Investigating insurance fraud using social media
Author :
Manuel Diaz-Granados;Javier Diaz-Montes;Manish Parashar
Author_Institution :
Rutgers Discovery Informatics Institute, Rutgers University, USA
fYear :
2015
Firstpage :
1344
Lastpage :
1349
Abstract :
Since the social media hype started in the early 2000s, the Internet has bloomed with user-generated data. The content generated by users in social media varies from blogs, forums, social network platforms, and video sharing communities. This data has a special emphasis on the relationships among users of the community. As a consequence, social media data contains significant information about their creators and people around them. For this reason, law enforcement and insurance companies, among others, are starting to explore ways of using this data to identify unlawful or fraudulent activities. In this work, we present a solution to extract and analyze social media data in pursuit of identifying insurance fraud. We describe and evaluate an initial prototype of our solution that has been implemented on top of the CometCloud framework. We show how our solution is driven by the insights obtained from the data and it is able to extract data relevant to the investigators.
Keywords :
"Insurance","Media","Data mining","Facebook","Companies","Twitter"
Publisher :
ieee
Conference_Titel :
Big Data (Big Data), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/BigData.2015.7363893
Filename :
7363893
Link To Document :
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