Data Journalism and Network Theory: A Study of Political Communication through <inline-formula><math display="inline"><semantics><mrow><mi mathvariant="double-struck">X</mi></mrow></semantics></math></inline-formula> (Formerly Twitter) Interactions

This study investigates the research questions: “<i>How do political connections within Greece’s governing party evolve, and what underlying patterns and dynamics are revealed through a network analysis of interactions on</i> <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="double-struck">X</mi></mrow></semantics></math></inline-formula> <i>(formerly Twitter)?</i>” To address these questions, data were collected from <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="double-struck">X</mi></mrow></semantics></math></inline-formula>, focusing on following, retweeting, and mentioning activities among the politicians within the governing party. The interactions were meticulously analysed using tools derived from Network Theory in mathematics, including in and out-strength centrality, hubs and authorities centralities, and in and out-vertex entropy. In line with the emerging field of data journalism, this approach enhances the rigour and depth of analysis, facilitating a more nuanced understanding of complex political landscapes. The findings reveal complex and dynamic structures that may reflect internal relationships, communication strategies, and the influence of recurring events on these connections within the party. This study thus provides novel insights into understanding political communication via social networks and demonstrates the applicative potential of Network Theory and data journalism techniques in social sciences.