Extracting Insights from Big Social Data for Smarter Tourism Destination Management

The technological revolution and the intense use of digital devices have allowed people to generate huge amounts of much heterogeneous data, called Big Data. Especially in the tourism field, Big Data has continuously been exploited for the management of Tourism Destinations and marketing strategies. In particular, the generation of that subset of Big Data, called Big Social Data, through the voluntary sharing of personal information and content generation on various online social networks, has created several opportunities for useful analysis for many tourism stakeholders, such as Destination Management Organizations (DMO), which can exploit strategic tools based on Big Social Data and analytics, for data-driven decisions with a growing emphasis on how generated insights are increasingly valuable when they come to anticipate visitor behaviour and shaping communication strategies. This paper aims at describing the comprehensive valuable insights into tourists' behaviour through the analysis of Big Social Data. Data considered in this work consists of large dataset from Flickr online social network and Twitter micro-blog. A Big Data Analytics framework, that implements multiple tasks such as topic extraction, geographical data clustering, time series modelling techniques, sentiment analysis and image analysis, is presented and it constitutes the innovative contribution of this work. Results show that the generated insights could allow DMO to use new knowledge about unknown clusters of Point Of Interests discovery, trend and seasonal patterns of tourist demand identification, e-WOM monitoring, attractive places identification that, in turn, will allow the DMO to address its needs in terms of decision support for the management and development of the destination, the enhancement of destination attractiveness, the shaping of new marketing and communication strategies, and the planning of tourist demand within the destination. The approach described in this paper is adopted in the NEST (NEtworking for Smart Tourism development, INTERREG-IPA CBC Italia-Albania-Montenegro) project which aims at enabling a cross-border cooperation between Albania, Italy and Montenegro, in order to create a common branding of the Adriatic-Ionian area as a smart tourism destination at a macro regional level and to develop common tourist routes and products.