The Rutgers Computer Science Department is pleased to share Professor James Abello Monedero and his team were awarded The Best Paper Award at the 13th International Conference on Data Science, Technology and Applications (DATA 2024).
The paper, titled” A Max Flow Min Cut View of Social Media Posts” addresses how viewing social media posts as a collection of directed triples { ⟨ Entity, Verb, Entity ⟩ } provides a frequency labeled graph with vertices comprising the set of entities, and each edge encoding the frequency of co-occurrence of the pair of entities labeled by its linking verb or verb phrase. The set of edges of the underlying topology can be partitioned into maximal subgraphs, called fixed points, each consisting of a sequence of vertex disjoint layers. We exploit this view to observe how information spreads on social media platforms. This is achieved via traces of label propagation across a Max Flow Min Cut decomposition of each fixed point. These traces generate a weighted label set system with an underlined label distribution, from which we derive a barycentric coordinatization of the collection of minimum cuts of each fixed point. This is a novel graph decomposition that incorporates information flow with a multi-layered summary of noisy social media forums, providing a comprehensible yet fine-grained summary of social media conversations.
To learn more, click on the video link: https://rutgers.box.com/s/bkjvm4clo45q7ccs1ujpg2j5ruzmqnqh
Additional Authors Timothy R Tangherlini (UC Berkeley), Haoyang Zhang (CS Rutgers).
