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oai:riuma.uma.es:10630/57222026-02-03T10:52:48Zcom_10630_2254col_10630_37953

00925njm 22002777a 4500 dc Del-Campo-Ávila, José author Moreno-Vergara, Natalia author Trella-López, Mónica author 2013 Social networks play an increasingly important role in shaping the behaviour of users of the Web. Conceivably Twitter stands out from the others, not only for the platform's simplicity but also for the great influence that the messages sent over the network can have. The impact of such messages determines the influence of a Twitter user and is what tools such as Klout, PeerIndex or TwitterGrader aim to calculate. Reducing all the factors that make a person influential into a single number is not an easy task, and the effort involved could become useless if the Twitter users do not know how to improve it. In this paper we identify what specific actions should be carried out for a Twitterer to increase their influence in each of above-mentioned tools applying, for this purpose, data mining techniques based on classification and regression algorithms to the information collected from a set of Twitter users. http://dx.doi.org/10.1016/j.procs.2013.06.059 http://hdl.handle.net/10630/5722 Redes de información Comunicación - Análisis de red Medios de comunicación social - Influencia Bridging the Gap Between the Least and the Most Influential Twitter Users