Few Recommendation systems for tourist sites are based on a user's profile's affinity compared to each place's description. The data collections to train these systems are from users and places in English-speaking countries. Considering the importance of Ibero-American countries in tourism, it is vitally important to generate Spanish resources that allow the generation of systems that help develop intelligent systems in tourism.

On the other hand, Sentiment analysis task in tourist texts has gained relevance in the last decade; however, the most significant scientific communication efforts have focused on the English language. Although some studies have focused on Spanish, few address Spanish who is not from Spain. These approaches are typically applied to collections taken from social networks such as tweets, so tourist texts have not been directly addressed.

Finally, the Epidemiological semaphore is a Mexican system implemented by the government to determine the activities allowed according to the severity of the covid pandemic. This system consists of 4 colors. Tourist activities are the most affected by any changes in the direction of the pandemic. Interestingly, many of the factors taken into account to determine the color of the semaphore are published in the news (hospital capacity, contagion curve, number of oxygen tanks, vaccinated population, etc.). In this way, the question arises if it will be possible to determine the color of the epidemiological semaphore in the future from published covid news.