Empowering an E-Government Platform Through Twitter-Based Arguments

KATHRIN GROSSE; CARLOS CHESNEVAR; ANA MAGUITMAN; ELSA ESTEVEZ

INTELIGENCIA ARTIFICIAL. IBERO-AMERICAN JOURNAL OF ARTIFICIAL INTELLIGENCE

Asociación Española para la Inteligencia Artificial

Lugar: Valencia; Año: 2012 vol. 15 p. 46 - 56

1137-3601

Social networks have grown exponentially in use and have gained a remarkable impact on the society as a whole. In particular, microblogging platforms such as Twitter have become important tools to assess public opinion on different issues. Recently, some approaches for assessing Twitter messages have been developed. However, such approaches have an important limitation, as they do not take into account contradictory and potentially inconsistent information which might emerge from relevant messages. We contend that the information made available in Twitter can be useful for modeling arguments which emerge bottom-up from the social interaction associated with such messages, thus enabling an integration between Twitter and defeasible argumentation. In this paper, we outline the main elements characterizing this integration in the context of a particular e-government platform (Decide 2.0). As a result, we will be able to obtain an "opinion tree", rooted in the first original query, in a similar way as done with dialectical trees in argumentation. The main contribution of this paper is the proposal of a method for building arguments from aggregated opinions. This leads to the design of a novel platform that makes it possible to explore collective opinions in a more meaningful and systematic manner.