Emotional Characterization of Rural Recreation Tourists Based on Big Data

In recent years, people’s consumption of the health industry has increased dramatically. The tourism industry will focus on the development of rural tourism and recreation tourism, as a new form of rural recreation tourism is also regarded as one of the leading directions of recreation tourism. This paper focuses on the study of tourists’ emotion visualization model based on big data, which first screens the textual topic words of rural recreation tourism based on the method of information gain and chi-square test and classifies different recreation topics after calculating the eigenvalues of the screened topic words based on IF-IDF. On this basis, the recuperation theme texts of different themes are preprocessed, while the emotional features embedded in the texts are extracted and empowered, and the emotional tendency of tourists towards rural recuperation tourism is explored based on the support vector machine model. Taking Kunming City as an example, among the positive emotional features of tourists towards Kunming’s rural recreation tourism, the highest frequency is “good”, with a frequency of 9,153, and most of them are praises for Kunming’s “scenery”. The words “average”, “disappointment”, “regret,” and “poor” are the negative emotions generated by the failure of certain scenic spots to meet the expectations of tourists. The study confirms the existence of time-emotional tendency differences and emotional preference demand differences among tourists in order to enrich the ideas and application value of this research field and bring more practical significance to tourist destinations.