AI based Sentiment Analysis of Visitors’ Perceptions Towards Urban Green Spaces in Kuala Lumpur, Malaysia

Urban green spaces (UGS) play a vital role in enhancing the quality of life and wellbeing of city dwellers by offering environmental, social, and health benefits. In rapidly urbanising cities such as Kuala Lumpur, Malaysia, assessing these public spaces from the users’ perspectives is essential to ensure they meet the needs and expectations of urban residents. This study explores visitors’ sentiments and perceptions of UGS by analysing online reviews sourced from Google Reviews. A total of 4 out of 19 UGS locations across Kuala Lumpur were examined, with data extracted using Python-based tools, specifically Selenium and PyCharm. The qualitative data were analysed using a combination of sentiment analysis and content analysis techniques powered by artificial intelligence (AI) and natural language processing (NLP) techniques. The study demonstrates the effectiveness of AI-driven tools for automatic text mining to extract meaningful insights from user-generated content. Based on the data analysis, the four parks achieved an average rating of 4.3 stars or higher, positioning them as exemplary benchmarks for the development and enhancement of future UGS projects in Kuala Lumpur. The findings highlight the value of integrating AI into urban studies to assess public sentiment efficiently and systematically. This approach offers urban planners and policymakers an innovative means to monitor the quality and effectiveness of UGS from the users’ viewpoint, ultimately contributing to more inclusive and responsive urban green space planning in Malaysian cities.