Spatiotemporal and Sentiment Analysis of Tourist Sources in Distinctive Pedestrian Street Using Social Media Data

Abstract

Tourism development plays a critical role in enhancing urban competitiveness and driving economic growth. However, research on pedestrian streets, which are important urban tourism destinations, continues to face challenges, such as limited data availability and insufficient attention to the dynamics of tourist sentiment. This study focuses on the Datang pedestrian street in Xi'an, using location-based social media data to analyze the spatiotemporal characteristics of tourist source market and the evolution of tourist sentiment. The results indicated that the sources of tourists evolved from predominantly local and high-GDP city business travelers to a nationwide dispersion, with the center of gravity shifting southeastward. The source structure exhibited three distinct states: discrete distribution, expanded distribution, and contracted distribution. Local tourists primarily engaged in leisure activities, while tourists from other regions emphasized participation. Sentiment analysis showed an annual increase in positive emotions from 2010 to 2017, followed by a decline from 2018 to 2023. The primary factors contributing to this decline include rising tourist numbers paired with diminished experiential quality, shifts in the tourism market alongside rising tourist expectations, external environmental factors, and developmental bottlenecks within the pedestrian street. Socioeconomic and regional demographic factors significantly impact the development of pedestrian streets. This study provides valuable insights for the reproduction of urban pedestrian street, promoting urban tourism and regional economic growth, enhancing urban renewal quality and efficiency, and shaping urban identity.