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Deiminari

Títol

Discovering Relevant Opinions in Twitter with Argumentation and Probabilistic valued relationships

Conferenciant

Ramon Bejar

Professor/a organitzador/a

Ada Valls Mateu

Institució

Universitat de Lleida

Data

05-12-2018 12:00

Resum

Dr. Bejar is associate professor at the department of Informatics and Industrial Engineering (UdL). He is a member of the Board of the Catalan Association for Artificial Intelligence (ACIA). His research is focused on Logics, Argumentation and Constrained Satisfaction problems. He will present his last work on the analysis of Twitter discussions. Twitter is one of the most widely used social networks when it comes to sharing and criticizing relevant news and events. In order to understand the major accepted and rejected opinions in different domains by Twitter users, we present an analysis system based on valued abstract argumentation to model and reason about the social acceptance of tweets in a discussion. We consider two different sources of information: the support for each tweet and the criticism/support relationship between tweets. The support for each tweet is mapped to a weight, and the criticism/support relationship between a pair of tweets is modeled with a probability vector. Our system also uses an uncertainty threshold probability, to filter our relationships that are considered to be not strong enough. Finally, the system uses a reasoning algorithm to discover the winning (accepted) tweets in a discussion.

Lloc

Aula A215

Idioma

Angls