Outdoor Environments, Public Health, and Well-Being

Parks play a critical role in the health and well-being of people in urban environments. Recent occurrences such as the Coronavirus (COVID-19) disease have underscored the importance of public parks, particularly in cities. In order to maximize the benefits of these spaces, it is important to understand the social dimension of site user experiences within successful urban parks.

Social media data provides a means to assess public places through the lens of large quantities of site users over time. This study uses 11,419 Tripadvisor reviews in a multi-step process, where qualitative content analysis builds upon Latent Dirichlet allocation (LDA) modeling topics to assess the semantic content of Bryant Park, New York.

Social Media Data and a Human-Centered Machine Learning Approach

This study applies extensive qualitative content analysis for a human-centric research approach after machine learning using LDA (Latent Dirichlet Allocation) Modeling. Significant interactions and connections between machine-selected topics were studied to understand site user experiences in Bryant Park. Additionally, this study proposes a preliminary analytical framework to provide a deeper and empirically based assessment of the experience of place in an urban park setting.

Topic Description

LDA topics included the following: T0 (Amenities) which focused on passive activity, relaxation, and the site features that enable and encourage people to take a seat and stay awhile;

T1 (Holiday Favorite) featuring the winter holiday season with a focus on season shops, specialty food vendors, and ice skating;

T2 (Summer Hotspot) centering on enjoyable summer activities and the vibrance of the park during the warm weather months;

T3 (Place to Relax) focusing on passive activity, relaxation, and the site features that enable and encourage people to take a seat and stay awhile;

T4 (General Overview) providing a general interpretation of the park space as a casual and typically pleasant experience.

A Framework for Urban Parks

A new framework emerged which specifies categorical information of site user perceptions and sentiment positivity. Site design elements are revealed as a major positive focus of site users, and reviews also centered on the position of the park within the urban fabric, site activity that consists of passive pastimes, and the essence of the space related to emotions. Findings can provide comprehensive guidance for designers and park managers for the creation of successful urban parks. It also provides another baseline for research of New York City’s parks.

A Framework for Urban Park Design through User Generated Data

In the context of a lingering global pandemic, it is important to understand successful urban parks from the perspective of the people who use them. The strong link between urban parks and human health and well-being places an increasing importance on better understanding what makes certain public spaces, such as Bryant Park, more beloved and highly used by the public.

The novel framework used in this study is based on overarching conceptual themes from Tripadvisor site user reviews over a nine-year time period, incorporating concept frequency and sentiment to quantify user experiences and perceptions.

The findings can help guide designers, planners, and park managers in the creation and management of successful urban parks by understanding what is desirable and important to the people.

In Collabration with

Texas A&M University, College Station, TX

Clmenson University, Clemson, SC

Dalian University of Technology, Dalian, Liaoning, CN

Huazhong Univerisity of Science and Technology, Wuhan, Hubei, CN

Team

Jessica Fernandez, Ph.D.

Yang Song, Ph.D.

Ruiqi Yang

Mary Padua, Ph.D.

Pai Liu, Ph.D

Runzi Wang

Tong Wang, Ph.D.

Publications

Fernandez, J., Song, Y., Padua, M., & Liu, P. (2022). A Framework for Urban Parks: Using Social Media Data to Assess Bryant Park, New York. Landscape Journal, 41, 15-29. https://doi.org/10.3368/lj.41.1.15

Song, Y., Wang, R., Fernandez, J., & Li, D. (2021). Investigating sense of place of the Las Vegas Strip using online reviews and machine learning approaches. Landscape and Urban Planning, 205, 103956. https://doi.org/https://doi.org/10.1016/j.landurbplan.2020.103956

Song, Y., Fernandez, J., & Wang, T. (2020). Understanding Perceived Site Qualities and Experiences of Urban Public Spaces: A Case Study of Social Media Reviews in Bryant Park, New York City. Sustainability, 12(19).

Awards

2023, Jury Recognition, Southeast Regional Conference. Jessica. F.; Yang. S;. Ruiqi, Y. New York, NY.