Abstract:
A full understanding of the local Azerbaijani web space is necessary to analyze
information flow patterns and influences in the local network and review the dependency
of Azerbaijan on external sources in case of cyber-attacks or national emergencies. To
develop this knowledge and to create efficiency in local data collection processes, a web
crawler with a subsequent graphical analysis is a must. The goal of this research is to
create a big graph of Azerbaijani web, analyze its linkages and most influential nodes. This
study aims to develop a catalog of local websites, create a web crawler to browse each web
page and outgoing links, construct a graph-based visualization with valuable information
and apply a ranking algorithm to measure the influence scores. A multiprocessing program
in Golang is developed to crawl the database of local webpages supplied by the Ministry
of Communication & Information Technologies. The program consists of a master,
multiple concurrent workers, and a Postgres database. The constructed graph consists of
nodes representing web pages, and edges which are connections in-between. A page
ranking algorithm is implemented to measure the importance of nodes. The observations
are such that the graph is not too strongly connected, and governmental web pages are the
most linked ones due to redirections to various services.