Remy is a second year PhD student advised by Dr. Alessandro Vespignani.
Her current research brings forward a network science approach to understanding the relational activity of thinking. By leveraging argument mining, networks of statements with propositional content connected by argumentative relations can be extracted from text data, representing the structures and processes of reasoning in domains ranging from self-deliberation to cooperative information-seeking dialogue, adversarial debate, consensus-seeking negotiation, rhetorical speech-making, and online discourse communities.
Applying the network science approach, novel research directions then emerge. Much like in ecological networks, the study of stress on systems of reasoning can enable a quantitative understanding of ideological transitions and domains of stability. The ideological space can be mapped a posteriori, rather than relying on the standard survey methods where pertinent questions are identified a priori and a one-dimensional ideological space is assumed; ideological groups and their relative distances can be identified by commonalities in the structure and content of reasoning. Argument schemes, templates for commonly encountered structures of argument, suggest an interesting application of the network motif approach, as the motifs and their functions are already well-defined.
Remy previously worked in the MOBS Lab on an Italian elections predictions project, and completed her Bachelor’s degree in Data Science at Northeastern University.
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