Time-based discovery in biomedical literature: mining temporal links

Political Rhetoric Through the Lens of Non-Parametric Statistics: are Our Legislators that Different?

“…In the future, we plan to incorporate a network component into a rhetoric analysis and to evaluate how the structure of legislative networks evolves over time. Possible algorithms for this future work can be found in the dynamic networks literature (Beykikhoshk et al, 2015;Loglisci, 2013). This is of particular interest in analysing presidential elections in the USA, as well as statements by terrorist organizations, and foreign political and social leaders, to name a few.…”

“…The behaviour of political actors is dynamic in nature and studying it requires statistical solutions that capture its temporal and spatial components. One such solution is provided by the dynamic networks literature (Loglisci, ; Loglisci et al ., ; Beykikhoshk et al ., ; Loglisci and Malerba, ). The focus is on the dynamics of evolving (heterogeneous) structured data (Loglisci et al ., ), as well as the dynamics of the content of textual data (Loglisci, ; Beykikhoshk et al ., ).…”

“…One such solution is provided by the dynamic networks literature (Loglisci, 2013;Beykikhoshk et al, 2015;. The focus is on the dynamics of evolving (heterogeneous) structured data , as well as the dynamics of the content of textual data (Loglisci, 2013;Beykikhoshk et al, 2015). Beykikhoshk et al (2015) proposed a flexible solution that does not restrict the type of changes that the model can capture, whereas developed a method based on two notions of patterns: emerging patterns and periodic changes.…”