Affiliation:
1. School of Architecture and Design, Beijing Jiaotong University, Beijing 100080, China
2. Horticulture and Landscape Architecture Department, Oklahoma State University, Stillwater, OK 74078-1015, USA
Abstract
Based on big data, a new public space evaluation method is proposed. Using programming technology to collect visitor reviews from the travel website TripAdvisor to build a database, based on the data of 99,240 words in 1573 visitor reviews in 10 years, the connection between data and reality is established through systematic data classification and visualization. Following an assessment of the Kimbell Art Museum’s functionality, architectural design, and landscape design, along with visitor feedback, a new evaluation methodology was formulated for application to public buildings with landscapes. By utilizing the unique advantages of big data, it provides convenient and efficient analysis methods for public spaces with similar data foundations and opens the way for the optimization of the built environment in the information age.
Reference34 articles.
1. Hutto, C.J., and Gilbert, E. (2014, January 1–4). VADER: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text. Proceedings of the International AAAI Conference on Web and Social Media, Ann Arbor, MI, USA.
2. Simmons, R.F. (1982, January 16–18). Themes from 1972. Proceedings of the 20th Annual Meeting on Association for Computational Linguistics, Toronto, ON, Canada.
3. A Machine Learning Approach to Sentiment Analysis in Multilingual Web Texts;Boiy;Inf. Retr.,2009
4. Zhu, X. (2005). Research on the Subjective Evaluation Method of Built Environment, Southeast University Press.
5. Post-Occupancy Evaluation: A Multifaceted Tool for Building Improvement;Vischer;Learn. Our Build. A State Pract. Summ. Post-Occup. Eval.,2002