Flowers as attractions in urban parks: Evidence from social media data
Introduction
Urban parks are an important part of urban ecosystems and urban landscapes. They play a vital role in maintaining the natural environment of cities as well as the stability of social systems (Chiesura, 2004) by contributing to the sustainable development of cities. Previous research has suggested that urban parks provide multiple benefits to human life. For example, urban parks provide both essential environmental services for urban residents and also significant social and psychological benefits enhancing mental health and well-being (Saw et al., 2015, Kim and Miller, 2019, Zhang and Tan, 2019, Buckley, 2020). They can also enhance the physical health of urban residents by providing space for exercise and social interaction (Kaczynski A T, 2007, Santos et al., 2016). The aesthetic, historical and recreational values of urban parks strengthen the attractiveness of cities (Chiesura, 2004), which is conducive for tourism and the local economy.
Urban parks have been an important topic in urban construction and management research. Most previous literature focuses on specific functions of urban parks, such as improving mental health (Coldwell and Evans, 2018), providing opportunities for leisure (McCormack et al., 2010), enhancing happiness (Kim and Jin, 2018), and releasing social pressure (van den Berg et al., 2010). Earlier research has also investigated the factors affecting park usage. These studies have shown that, for instance, park size and the distance visitors are willing to travel affect the frequency of park visits (Schipperijn et al., 2010). Also, the living context and quality of vegetation influence the satisfaction levels with urban parks (Zhang et al., 2015). At the same time, the presence and quality of park facilities (McCormack et al., 2010), and the number of organized activities (Cohen et al., 2010) are conducive to encouraging park use. Also, other factors such as traffic convenience, the socio-demographic traits and visit-related preferences of users influence park visitation (Swapan et al., 2017, Guo et al., 2019, Mak and Jim, 2019). While most of the earlier studies on urban park visitation have relied on traditional survey data, which are limited to specific sample populations and, thus, hard to generalize beyond the survey respondents, more recent studies have begun to take advantage of the possibilities offered by big data.
Due to the rapid development of communication and information technologies, new data sources, in particular social media data, have become available that provide novel material for researchers in understanding human behavior in urban parks. Such data contain a wealth of information about visitors’ behavior and experiences, and also furnish opportunities to study topics such as behavioral patterns and recreational preferences (Song et al., 2020a, Song et al., 2020b), factors affecting visitation frequency (Zhang and Zhou, 2018, Guo et al., 2019, Song et al., 2022), and landscape design quality within urban parks (Song and Zhang, 2020). Social media data have been proven to reliably represent the frequency of park visitation (Tenkanen et al., 2017, Song et al., 2020a, Song et al., 2020b). This novel type of data has been used to investigate visitors’ activities in (Roberts, 2017) and opinions of urban parks (Roberts et al., 2019), as well as to understand the driving factors behind urban park visitation (Donahue et al., 2018).
In the context of global climate change, many scholars have begun to focus on parks, a relatively small-scale type of urban green spaces. Only a few studies have, however, associated phenological phenomenon with park visitation and tourism and explored their connections. In recent years, tourism activities based on ornamental plants have become popular tourist attractions (Tao et al., 2015). Many ornamental activities held in parks, for example, around the time of peach and cherry blossoms have attracted large numbers of visitors to urban parks and generated considerable economic benefits for the surrounding local economy. For example, the 36th China Luoyang Peony Cultural Festival in 2018 received 26.473 million visitors and generated an estimated value of 24.196 billion yuan in tourism revenue (Luoyang Municipal Culture, Radio, Television and Tourism Bureau, 2018). In the same year, the 69th Keukenhof Flower Show attracted more than 1 million visitors from more than 100 countries and circa 75% of the visitors came from abroad (Sohu News, 2019). Holding flower viewing activities, thus, seems to attract extensive numbers of visitors to urban parks, but at the same time might also threaten their limited carrying capacities. Therefore, we argue that, as an important element of park visits, flowers are of great significance to the management of urban tourism in many cities.
A considerable amount of research has investigated the effects of plants from the ecological and environmental perspective based on phenological observation data (Gao et al., 2018, Yu et al., 2019). Some studies have also explored the impact of changes in phenological periods on tourism management (Ma and Fang, 2006, Zang et al., 2020), and assessed the influence exerted by changes in plant phenological events on visitor volumes (Liu et al., 2019a, Liu et al., 2019b). Nonetheless, to the best of our knowledge, there is no previous research exploring the association between ornamental plants and visitor volumes to urban parks based on social media data. Since social media data have been shown to accurately and efficiently represent floral phenological characteristics associated with tourism and park visitation (Liu et al., 2019a, Liu et al., 2019b), the data offers us the possibility to explore the influence of flowers on park visitation patterns. Therefore, we propose a framework to study the association between the number of visits and flower viewing events by utilizing natural language processing techniques to extract information about visitors’ flower appreciation activities from social media data. We test the framework with data from Beijing municipal urban parks. Our aim is to address the following questions:
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Is there a connection between flowers and visitor volumes to urban parks?
And if there is a connection:
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Are there differences (in this connection) between different types of urban parks based on their seasonal visitation characteristics?
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Are there differences (in this connection) between different kinds of flowers in urban parks?
Our findings provide advice for the design and management of urban parks by underlining the seasonal imbalance in visitor flows and by discussing how to facilitate park visitation (and tourism) in connection with flower viewing.
Section snippets
Social media data and park research
Traditional methods used to gather data in park research include interviews, questionnaires and behavioral observations (Zhang et al., 2015, Huang et al., 2020, He et al., 2022). Such methods, however, are usually time-consuming, site-specific and limited in their coverage (Sessions et al., 2016). Moreover, these methods have been noted to have weaknesses in terms of their inaccuracy and inefficiency in estimating the visitor volumes to urban parks. As a result, visitors’ behavior
Research framework for analyzing visitors’ phenological behavior
We propose a research framework, shown in Fig. 1, for analyzing visitors’ behavioral features with phenological information extracted from social media data. We chose microblog data from Sina Weibo as our data source and designed data collection and processing (cleaning) rules. In order to comprehensively analyze the connection between flowers as attractions and urban park visitation, we divided the research contents into two sections: (1) “phenological information extraction” and (2) “visitor
Time variation characteristics of visitors visiting the park
As stated above, our microblog data covers the full years from 2012 to 2019. We further divided the microblog data by day to calculate the daily Chinese visitor volumes to Beijing municipal urban parks (i.e., the total number of visits by Chinese visitors in all parks), as shown in Fig. 4.
(Each column represents a feature vector that summarizes the visitor volumes to Beijing municipal urban parks on each day of a given month. Darker color represents higher visitor intensity. Naturally, there
Flowers as a tourist attraction
A wide range of factors can influence park visitation, including organized activities (Cohen et al., 2010), accessibility (McCormack et al., 2010) and pursuit of well-being (van den Berg et al., 2010, Coldwell and Evans, 2018), etc. However, there remains a gap in the research on the potential connection between flowers and park visitation. Our results show that flowers are an important attraction for visiting Beijing municipal urban parks: flowers have a non-negligible correlation with the
Conclusion
In this paper, we proposed a framework for analyzing phenological information extracted from social media data to explore the floral viewing behavior of urban park visitors. We applied the proposed framework (Section 3) to Beijing municipal urban parks and used microblog data as an indicator of visitor volumes to urban parks. Our main findings (based on correlation and co-word analysis) can be summarized as follows:
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Flowers are an important part of the total attractiveness of urban parks: there
CRediT authorship contribution statement
Naixia Mou: Methodology, Writing – original draft, Project administration, Funding acquisition. Jinhua Wang: Data curation, Visualization, Writing – original draft. Yunhao Zheng: Validation, Writing – review & editing. Lingxian Zhang: Writing – review & editing. Teemu Makkonen: Writing – review & editing. Tengfei Yang: Data curation, Supervision. Jiqiang Niu: Writing – review & editing.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
This work was supported by the National Natural Science Foundation of China [grant number 42171460], and the Open Fund of Key Laboratory for Synergistic Prevention of Water and Soil Environmental Pollution [grant number KLSPWSEP-A09].
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