Davide Vega D'Aurelio

Measure development and social media analysis using temporal text networks

The widespread social media usage generates an immense amount of data. Data which is highly beneficial to several domains whether monetary or research based. Various models exist to extract this data however analysis tend to be restrictive. The temporal text network model is a dynamic network model built upon the foundation of temporal networks. It provides text as a variable and considers messages passed between users while maintaining the time of transmission, making it suitable for social media analysis. No measures exist to perform this analysis, the objective of this thesis was therefore to develop measures to be used in the mapping of communicative behaviour on two Twitter datasets. The created measures conclude that communication is similar on Twitter no matter the domain observed. When further reducing the scope of a political dataset, information regarding the social media presence between parties and the localization of key questions was found.