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Tourism industry and the Big Data, at first sight, may not be two areas that seem to have much in common. But the reality is that today the former takes advantage of a lot of the technology provided from the latter, to continue growing and improving the services.
Big Data is currently the best ally to continue being number one on the international tourism industry podium, thanks to the improvement of services and the maximum adaptability to the needs of its visitors.
Social networks and new tourism portals that rely on the collaboration of users have become one of the main references when evaluating or planning a trip. For this reason, it is essential for companies dedicated to tourism to know what is going on in these platforms in order to check the pulse of both their clients, as well as potential customers.
It is vital to monitor all these opinions and experiences that tourists are leaving behind like a digital fingerprint, and for that, the right tools are needed. There is no doubt about the importance of analyzing the reputation that is created spontaneously in social networks or in specific tourism portals because, in addition, the opinion of a user is conditioned by that of other people. And more if those people have some social influence or act in a close environment.
The technology of sentiment analysis is one of the typical tasks of natural language processing (NLP), which manages the detection of positive, negative and neutral comments written in natural language with a high degree of reliability.
These emotions, opinions and feelings are extracted from the content poured by visitors and users into social networks and tourist analysis platforms. This procedure is performed automatically through a sentiment analysis engine. Basically, there are two models of NLP: Linguistic, based on grammars, and Probabilistic, based on data. Within linguistic models, there are different degrees of depth. In the lexical analysis, the engines reach a more superficial level, classifying as positive or negative according to common words like great, horrible, etc… But there are analyzes that go deeper into understanding the meaning of words using morphological, syntactic or contextual information.
In these more complex analyses, the models are able to recognize positive text structures with negative words, or recognize idiomatic uses, solve anaphora… This profound analysis is, without a doubt, a revolution for the tourism industry that, thanks to this processed information, can empower and improve its services to the maximum.
The numbers speak for themselves. In 2016, once again, the seventh consecutive year, number of international tourist arrivals (overnight visitors) grew by 3.9% and reached a total of 1,235 million worldwide. These data highlight the impact of tourism industry on the global economy.
Companies in the sector are aware of their role as leaders in the market. That’s why they have recognized Big Data as the best weapon to continue being at the forefront of international tourism. This relationship that has emerged between both areas promises to be durable and become a solid partnership, highly beneficial for tourism in the country.
Source: tourism-review.com