Perez Cabañero, CarmenBigne, EnriqueRuiz Mafe, CarlaCuenca, Antonio Carlos2020-07-292020-07-292020-05-129788490488324https://riunet.upv.es/handle/10251/148826[EN] Given the importance of electronic word of mouth (eWOM), this paper analyses the content of messages generated by users related to a tourist destination and shared through Twitter. We propose three research questions regarding eWOM behaviour in Twitter focused on the expertise of the reviewer, sentiment analysis of a tweet and its content.In order to address those research questions we carry out text mining analysis by retrieving existing information on Twitter (over 1500 tweets) regarding to Venice as a tourist destination.Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)Web dataInternet dataBig dataQcaPlsSemConferenceTwittereWOMTourismSentiment analysisCapítulo de libro10.4995/CARMA2020.2020.11621Abierto