Paper Info
Title
Supporting Law Enforcement in Digital Communities through Natural Language Analysis
Abstract
Recent years have seen an explosion in the number and scale of digital communities (e.g. peer-to-peer file sharing systems, chat applications and social networking sites). Unfortunately, digital communities are host to significant criminal activity including copyright infringement, identity theft and child sexual abuse. Combating this growing level of crime is problematic due to the ever increasing scale of today's digital communities. This paper presents an approach to provide automated support for the detection of child sexual abuse related activities in digital communities. Specifically, we analyze the characteristics of child sexual abuse media distribution in P2P file sharing networks and carry out an exploratory study to show that corpus-based natural language analysis may be used to automate the detection of this activity. We then give an overview of how this approach can be extended to police chat and social networking communities.
Year
DOI
Venue
2008
10.1007/978-3-540-85303-9_12
IWCF
Keywords
Field
DocType
social networking site,natural language analysis,law enforcement,digital communities,digital community,significant criminal activity,copyright infringement,child sexual abuse media,automated support,chat application,social networking community,child sexual abuse,p2p file,file sharing,identity theft,social networks,p2p,social network,exploratory study,network monitoring
Internet privacy,Social network,Child protection,Computer science,Identity theft,Copyright infringement,Network monitoring,Law enforcement,File sharing,Exploratory research
Conference
Volume
ISSN
Citations 
5158
0302-9743
11
PageRank 
References 
Authors
1.38
4
8
Name
Order
Citations
PageRank
Danny Hughes138549.25
Paul Rayson253854.59
James Walkerdine328925.56
Kevin Lee434027.53
Phil Greenwood534820.93
Awais Rashid62041149.78
Corinne May-Chahal7282.66
Margaret Brennan8111.38