The news media play a crucial role in providing citizens with high quality information that leads to the formation of public opinion. They also serve as “watchers” by monitoring the activities of the public institutions. We notice a trend where governmental administrations are increasing their transparency by publishing their data freely on the Internet. This creates opportunities for data journalists to look for stories by analyzing these vast quantities of data and to monitor the public authorities even closer.
Social network analysis (SNA) as a method is widely used in sociology to formalize and study structures and flows of communication within communities. Recent advances in computer science have made it possible to automate these analyses, allowing for the study of large-scale networks. The added value of social network analysis methods in the field of data journalism is that it helps to analyze the relationships between the actors instead of focusing on the actors themselves.
We already have a case study analyzing data on public procurement with the goal of detecting possibly corruptive connections between public institutions and commercial organizations. Because there has been no prior work in analyzing public procurement from a social network perspective, the research represents an innovative approach. In the journalistic field, the described method can be used in order to analyze the attributes of the mutual relationships and connections of the actors instead of only the attributes of the actors themselves. Therefore, we consider our method to be a useful addition to the data journalism toolkit.
We are currently looking for funding to expand this research to other countries in Europe. We are proud the have found De Correspondent and Wired Italy to be our supporting partner in this.