PolarityRank: Finding an equilibrium between followers and contraries in a network

Day - Time: 06 June 2012, h.11:00
Place: Area della Ricerca CNR di Pisa - Room: C-29
  • Fermín Cruz Mata (Departamento de Lenguajes y Sistemas Informáticos - Universidad de Sevilla (visiting ISTI-CNR throughout June 2012))

Fabrizio Sebastiani


In this talk I will present the random-walk ranking algorithm named PolarityRank. This algorithm is inspired in PageRank, and generalizes it to deal with graphs having not only positive but also negative weighted arcs. Besides the definition of the algorithm, I will show a pair of problems we have addressed through it: automatic expansion of opinion lexicons and trust and reputation computation in social networks. I intend to convey the idea of which problems are suitable to be solved using PolarityRank. It can be summarized in three prerrequisites: the problem has to be representable using a graph, where nodes are some entities and arcs represent some relations between them; some a-priori information must be available for a subset of the entities, and also about the "similarities" and "differences" between them (in terms of what that information represents); and the solution of the problem might be seen as a propagation of the a-priori information, consisting of a set of induced values for the rest of entities.