12-17, 11:30–11:45 (Asia/Bangkok), Auditorium Hall 2
This study explores the integration of Natural Language Processing (NLP) and Geographic Information Systems (GIS) to analyze the spatial distribution and sentiment of restaurants based on TikTok data. Data was collected from TikTok using primary and secondary hashtags related to restaurant reviews in Bangkok. The resulting database enabled a detailed analysis of restaurant locations and customer sentiment using Logistic Regression for sentiment analysis. The findings indicate that negative reviews were predicted with the highest accuracy (84%), followed by positive (78%) and neutral (76%) reviews. The spatial analysis identified a dense of restaurants in the inner districts of Bangkok. This integration of NLP and GIS not only mapped the popularity of restaurants as mentioned on TikTok but also provided significant insights into consumer behavior and preferences. The study demonstrates the effectiveness of combining NLP and GIS for geospatial analysis, offering a powerful tool for understanding social media trends and their impact on local businesses. The results underscore the potential for leveraging social media data to inform urban planning and business strategies, particularly in the context of food and hospitality industries.
