Biblio
Deep web refers to sites that cannot be found by search engines and makes up the 96% of the digital world. The dark web is the part of the deep web that can only be accessed through specialised tools and anonymity networks. To avoid monitoring and control, communities that seek for anonymization are moving to the dark web. In this work, we scrape five dark web forums and construct five graphs to model user connections. These networks are then studied and compared using data mining techniques and social network analysis tools; for each community we identify the key actors, we study the social connections and interactions, we observe the small world effect, and we highlight the type of discussions among the users. Our results indicate that only a small subset of users are influential, while the rapid dissemination of information and resources between users may affect behaviours and formulate ideas for future members.
With increasing monitoring and regulation by platforms, communities with criminal interests are moving to the dark web, which hosts content ranging from whistle-blowing and privacy, to drugs, terrorism, and hacking. Using post discussion data from six dark web forums we construct six interaction graphs and use social network analysis tools to study these underground communities. We observe the structure of each network to highlight structural patterns and identify nodes of importance through network centrality analysis. Our findings suggest that in the majority of the forums some members are highly connected and form hubs, while most members have a lower number of connections. When examining the posting activities of central nodes we found that most of the central nodes post in sub-forums with broader topics, such as general discussions and tutorials. These members play different roles in the different forums, and within each forum we identified diverse user profiles.