Urban Data management represents a major challenge
in the field of Smart Cities. Its understanding is essential for
the development of better smart services, which are a persistent
demand in urban policies. From all the sources of data available,
those that involve a collective processing of urban information
(by the citizens or other collectives) deliver in fact, useful insights
into social perception. Such is the case, for example, of data
collected from mobile networks. Prior to the design of sociotechnical
artifacts in cities, it seems important to extract the
qualitative and quantitative opinions, sentiment and feedbacks
present in these data. In this paper we present three solutions for
mining these contents through Knowledge Extraction methods,
as a previous step to the prospection of new smart services.Ministerio de Economía y Competitividad TIN2013-41086-
