Εξόρυξη Δεδομένων, Κοινωνικά Δίκτυα και Τουρισμός

Abstract

All actors involved in the tourism industry and providing cultural and tourism information as well as other related services should be able to establish relationships between tourism activities and tourist preferences in order to design and offer more attractive tourism packages. Especially in Greece, where tourism is its most important economic sector and its total contribution to the economy amounts to between 37 and 45 billion, ie more than 20% of the country's GDP. A detailed analysis of the operation of the tourism industry is therefore needed in order to make strategic planning decisions in the future. To make this possible, the need for data mining is more urgent than ever. According to Bose and Mahapatra (2001) from the University of Hong Kong, data mining can be used in three key areas of tourism, specifically: 1. Expenditure forecast for tourism 2. Analysis of the tourism profile in a target group and 3. Forecast of the number of tourist arrivals. Social media, which in the last decade have very actively penetrated into our lives, are a rich mine of large-scale data mining for tourism. The term social media could generally be understood as Internet applications, which include user-generated content related to the experiences gained from a travel destination so that other users can easily access it. Social media thus include a myriad of applications that allow individual users to post and highlight their impressions, experiences, adventures and even unconfirmed rumors on the Internet. This large collection of information is increasingly benefiting prospective tourists, while making it increasingly difficult for businesses to market tourism. This paper aims to highlight the particular challenge and opportunity to analyze a huge amount of data, offered through social media, and which is modeled, selected and explored to identify understandable and useful information for the optimization of the tourism industry. It is divided into two parts, where in the first part it brings the reader into a first contact with the science of big data, Data Mining, social media and tourism. A complete conceptual approach to the above terms is provided, as well as the characteristics of big data, the stages of data mining and the techniques used to extract useful information from them. In addition, the evolution and importance of social media in terms of data mining and the challenges we are called to face are presented. The first part concludes with the evolution of the analysis of the tourism industry, as it begins to become an important part of national economies after World War II, and how we were led to its analysis based on data. The second part analyzes the application of big data in tourism and the benefits arising from their use. The role and importance of large-scale data mining through social media to increase the efficiency and effectiveness of the tourism industry is examined. In addition, the data mining techniques used to extract useful knowledge from the content created / posted by users on social media related to tourism are presented, for example texts and photos. Finally, an attempt is made to identify the challenges and future directions of data mining from social media to optimize the tourism industry. This paper concludes by presenting conclusions on the above issue. In conclusion, the utilization of large online data to optimize the tourism package offered is still in its infancy, however large travel companies are increasingly trying to take advantage of the large-scale data mining generously offered by social media users and the information that emerges from them.