For landscape architects to design successful public places, it is critical to understand the human perspective behind celebrated outdoor built environments.
Using the case study of the High Line Park, this research utilizes a large dataset of social media reviews over the course of seven years, combining machine learning techniques with qualitative assessment to decipher why people are drawn to this linear park.
LDA is a generative statistical model that fits each document with a distribution of underlying topics and each topic with a distribution of underlying topic terms.
Among 15 topics, T0 (Best time to visit), T1 (Attachment and satisfaction), T2 (Away from traffic), T4 (General perceptions), T8 (Walking and viewing) and T12 (Activities) are related to user experiences which demonstrate users’ attitudes, emotions and behaviours associated with the park visit.
T3 (Accessibility and guidance), T6 (Park features), and T9 (Planning and design) are topics with reviews that specifically comment on how the park was designed and planned.
T5 (Historical transformation) and T11 (Vernacular culture and locals) talk about the historical and cultural background of the site. T7 (Location and nearby attractions) and T14 (Attractions seen from HLP of NYC) mention the significant locations, surrounding amenities, and physical features such as a subway, restaurants, markets, and the rivers.
T10 (Well maintained) and T13 (Park services and amenities) address park management concerns such as landscaping, facility maintenance, food accommodation services, and art display programs.
We conclude that visitors’ appreciation of the park regardless of season is linked with the park’s history, design, and management. The historical transformation aspect of the HLP is a highly recognized concept by visitors as a brilliant idea to convert a railway track to a park. Pleasant walking and viewing experiences allow visitors to escape from the busy city life, thanks to the park’s prominent design features, and the unique location and physical characteristics. Excellent park management and services ranging from amenities to onsite living performances are also a big part of the sustained success of the HLP.
Findings suggest fifteen different topics that can be used as a research-based framework for understanding its success and can help inform future public space design.
This research delivers an in-depth analysis of user experiences and emotional connections with urban green spaces, focusing on The High Line from 2011 to 2018. Utilizing a large dataset of 34,060 Tripadvisor reviews, the study captures the nuanced perspectives of visitors, highlighting the factors that continuously draw millions to the park. This empirical knowledge serves as a critical resource for decision-makers and planners, informing future urban revitalization and greenway projects. The findings not only underscore the importance of user-centered design but also offer transferable insights for similar initiatives in other urban contexts, contributing to the broader field of sustainable urban development.
Why Do We Love the High Line Park: A Lesson from Big Data
Urban greenways have become a popular development theme for cities in the U.S. and around the world. The High Line park (HLP) in New York City is one of the most successful contemporary greenway parks, inspiring urban planners, designers, and public administrators worldwide.
This study provides a comprehensive understanding of user experiences in a long-term time frame (2011-2018) through the lens of online reviews. Using a mixed-methods approach, we conducted Latent Dirichlet Allocation (LDA) topic mod- elling to quantitatively identify the key topics that represent 34,060 reviews and 30,285 users, followed by qualitative analysis to inductively interpret the LDA topics.
HLP’s unique location and physical advantages, thoughtful planning and design, and conscientious park management all contribute to these desirable experiences. The study also helps inform future decision-making and planning & design practices for urban revitalization and greenway projects.
In Collaboration with
Texas A&M Univerisity, College Station, TXHuazhong University of Science and Technology, Wuhan, Hubei, CNMichigan Technological University, Houghton, MITeam
Ruiqi Yang Yang Song, Ph.D.Jessica Fernandez, Ph.D.Tong Wang, Ph.DHongmei Lu, Ph.D.Publications
Song, Y., Yang, R., Lu, H., Fernandez, J., & Wang, T. (2023). Why do we love the high line? A case study of understanding long-term user experiences of urban greenways. Computational Urban Science, 3(1), 18. https://doi.org/10.1007/s43762-023-00093-y Awards
2024, Merit Award. ASLA-NY Design Awards. Ruiqi, Y. (Student); Jessica. F. (Advisor); Yang. S. (Advisor); Tong, W. (Advisor). New York, NY. https://www.aslany.org/2024-asla-ny-design-awards/2023, Student Award for Research. Council of Educators in Landscape Architecture (CELA). Ruiqi, Y. (Student); Jessica. F. (Advisor); Yang. S. (Advisor); Tong, W. (Advisor). St Antonio, TX.2023, Jury Recognition. Southeast Regional Conference. Ruiqi, Y. (Student); Jessica. F. (Advisor); Yang. S. (Advisor); Tong, W. (Advisor). New York, NY.