CAPER: Crawling and analysing Facebook for intelligence purposes

Abstract

Organised crime uses information technology systems to communicate, work or expand its influence. The EU FP7 Security Research Project CAPER (Collaborative information, Acquisition, Processing, Exploitation and Reporting for the prevention of organised crime), created in cooperation with European Law Enforcement Agencies (LEAs), aims to build a common collaborative and information sharing platform for the detection and prevention of organised crime, which exploits Open Source Intelligence (OSINT). LEAs are becoming more inclined to using OSINT tools, and particularly tools able to manage Online Social Networks (OSNs) data. This paper presents the CAPER Facebook crawling and analysis subsystem. Heuristic algorithms have been implemented in order to extract specific properties of Facebook's social graph, in particular user interactions. To support analysis tasks specifically, extensive effort has been spent on the analysis of textual user generated content and on the recognition of named-entities, in particular person names, locations and organisations. Relationships between users and entities mentioned in posts and in related comments are created and merged into the users networks extracted from the social graph. All entity relationships are finally visualised in userfriendly network graphs.

Using Open Source Intelligence as a Tool for Reliable Web Searching

“…All agency interactions are eventually visualized in user-friendly network graphics. However, this paper only focused on a single social media platform which is Facebook for target search and information extraction unlike our paper which covers the entire web platform [6].…”

Experiencing the Detection of Radicalized Criminals on Facebook Social Network and Data-related Issues

“…Some research efforts have been conducted by employing SNA, such as in [45] where, starting from the monitoring of user's activities of terrorist groups on Facebook, an algorithm, based on a centrality approach, has been proposed to discover the most active users in the group, who were able to recruit the highest numbers of new users. In [46] instead, a system for crawling and analysing organized crime communities on Facebook has been proposed. Specifically, different heuristic algorithms have been implemented in order to extract specific properties (i.e.…”

How Data Mining and Machine Learning Evolved from Relational Data Base to Data Science

“…The proliferation of easily and quickly accessible social media data can be used by researchers for many different purposes. For example, such data has already proved useful for many scenarios such as that of emergency management [13] [12], intelligence [3], eHealth [31], and social networks security [28] [29], to name but a few. In recent years, we have observed the explosion of image-sharing services such as Flickr and Instagram.…”