Examining the Climate Sensitivity of Tourists in South Africa Using TripAdvisor: A Big Data Approach Through Web-Scraping

Abstract

The viability and competitiveness of tourism locations depends, in part, on weather and climate. Climate determines tourists’ choice of locations, activities, and vacation lengths. Netnographic research utilising TripAdvisor reviews can objectively evaluate tourists’ climatic sensitivity and determine the meteorological factors most important to them. Manually reading and coding hundreds of reviews is, however, time-consuming. Web-scraping, which is the process of obtaining large amounts of data from various websites, can automate this process to analyse hundreds of thousands of reviews nationwide and evaluate climatic influence more comprehensively. This thesis compares the outputs of manually collected and web-scraped TripAdvisor reviews, to evaluate the efficacy of a web-scraping approach. A comparative analysis of TripAdvisor reviews collected through manual and web-scraping methods was conducted for 19 South African tourist destinations. The objective was to assess the efficacy of web-scraping when exploring weather-related data. The two methodologies demonstrated a 3.5% difference in the total number of climatic occurrences. Although there were significant variations in the number of climate mentions in three locations, namely East London, Polokwane, and Knysna, no statistically significant differences were calculated between the two methodologies in terms of the total number of climate mentions. Web-scraping has been demonstrated to be an efficient method for the real-time collection of big data- which is large volumes of data sets that are generated at high speeds that cannot be handled effectively by traditional processing methodologies and has provided a comprehensive understanding of the sensitivity of tourists to climate. Sentiment analysis revealed that tourists expressed negative or extremely negative sentiments regarding the majority of weather scenarios, with the exception of good weather, mist, and hail. To comprehend the impact of climate on tourist perceptions, regional variations in the frequency and proportion of weather-related mentions were investigated. Cold, hot, and rainy weather were the most frequently mentioned weather conditions in South Africa, with significant regional variations. Cold conditions were most frequently mentioned in Gauteng, cloudy weather in the Western Cape, windy conditions in Mpumalanga, thunderstorms in the Eastern Cape, and hot weather in the Northern Cape. These results indicate that weather significantly influences tourist experiences, and web-scraping is a viable method for obtaining these insights. It has been shown that online scraping is an efficient method of acquiring large quantities of real-time data and providing a full understanding of visitors' sensitivity towards climate. Consequently, it may be considered and accepted as a reliable means of data collection, facilitating more comprehensive and widespread analyses of tourists’ climatic sensitivity from TripAdvisor review.