02.521: Urban Data & Methods I Irwan Soetikno / Lee Ke Wei (Tommy Kevin) / Lim Swee Kiat SUTD MUSPP - 15 December 2018
Waterfront and the City:Public Life at
Marina Bay Promenade, Singapore
CONTENTS
01. Introduction 02. Research Questions 03. Literature Review 04. Methodology 04.1Fieldwork covers the Boardwalk 04.2 Analytics covers the Promenade 05. Findings 05.1 Boardwalk 05.2 Event Plaza 05.3 Lotus Pond 05.4 Sunbathing deck 05.5 Instagram 05.6 Twitter 06.Discussion 06.1Photographic use of space: Icons Far and Near 06.2 Space Popularity 07. Limitations 08. Reflections 09. Conclusion References Appendix
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01. Introduction
The Marina Bay area was planned since 1992 as the crème de la crème representation for work and play. A key ingredient in successful implementation that is universally applicable is the long term planning, but technological changes often outpace planning ability. Today, Marina Bay has become the premier destination for both business and pleasure in the city-state, after more than two decades of planning and implementation. The crown feature of Marina Bay is the promenade along it (hereafter, “the Promenade”), the embodiment of Singapore as a prosperous global citystate, but was planned prior to the advent of the digital age. 2
Figure 01. Site Location and Context
The ubiquity of smart phones and social media use in everyday life has significantly changed the ways spaces are used (Farman 2012), with social media environment adding digital layers of interaction and meaning making to that in the physical space provided by the built environment. Hence, we posit that the presence of two sets of urban spaces at one location: the physical and the cyber, and are interested in documenting their spatial use patterns. We test this hypothesis first by employing the ethnographic method in the style of Whyte (1980) to document public life, perceptions of and space use along the promenade. This enduring technique is complemented with data analytics performed from data crawled from the social media platforms that 3
relates to the use of the Promenade. We seek to find out what are the similarities and differences in space use patterns and social behaviours between the physical and the cyber. Through a timely update of Whyte’s classic methods in urban studies with the latest data techniques to further the efforts towards an urban science, we hope this paper may further an understanding on the effectiveness and impact of design on public space use, as well as to undertake theoretical contributions in the study of public life in planned urban spaces, through making meaningful distinctions of having two spaces at one location at the same time.
02. Research Questions Primary Question
How do people use the Marina Bay Promenade? Sub-questions
What are the space use patterns along the Marina Bay Promenade? What are the similarities and differences in usage patterns and social behaviours between the physical and the cyber spaces?
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03. Literature Review Marina Bay was planned for dual purposes: a reservoir for urban water catchment and a flood control as well as the creation of an iconic waterfront in the downtown core for city’s liveability. Much has been written on its urban planning (Tortajada et al 2013), the technical functions for water management and sustainable development (Wong & Brown 2009:680, Tan et al 2008), and its water quality (Xu et al 2011, Nguyen et al 2012). However, there is a lack of literature on its socio-urban analysis although such studies exist for the stretch of waterfront along Singapore River (Huang & Chang 2003, Chang & Huang 2005), prior to the completion of the promenade.
04. Methodology Two distinct tool kits are employed, one for the study of the physical space and the other for the cyber space. Per Whyte’s method for analysing small urban spaces (1980), videography, time-lapse photography, and the direct observation are used. Fieldwork was conducted at the Boardwalk (thereafter referred as “the Boardwalk”) fronting the Marina Bay Sands (Figure 02), part of the 3.5km Promenade continuous circulation loop surrounding the Marina Bay, itself part of the bigger realm of planned public urban spaces developed from 2007 to 2012. Fieldwork was done in November 2018, twice for weekday from 12 to 8pm and once on weekend from 12 to 8pm.
Figure 02. Site Coverage. Left: Analytics covers the Promenade. Right: Fieldwork covers the Boardwalk
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04.1Fieldwork covers the Boardwalk
The site area for fieldwork takes places at the Boardwalk, which is the busiest and most diverse 700m stretch of the promenade, while the analytics component can capture big data for the entire promenade. The Boardwalk links the observed areas together into the larger outdoor premises, and connect the MBS complex with Marina Bay sitting gallery in the north and Marina Bay Financial Centre in the south. Within the Boardwalk, direct observation was divided into three areas. The classification is selected because these areas see the highest volume of outdoor space-use: congregating, resting, sight-seeing, photo taking (including selfies) as individual spaces but also seamlessly come together as part of the larger Boardwalk. These three areas are: The Lotus Pond, the outdoor feature on the ground floor of ArtScience Museum; The Event Plaza, the timber deck in front of the entrance to The Shoppes; and the Sunbath Deck, the timber deck with sunbath chairs, located at the southern edge. The interior space-use at MBS is not part of the purview. Although it is also a public access space, we consider it the domain for private place-making affairs of the company for the purposes of optimizing its mall, hotel, and convention centre operations. The Boardwalk is the outdoor space that is part of the public urban space provision for the Marina Bay, and the aim of the fieldwork is to document its space use as such.
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Figure 03. The Areas of Observation
04.2 Analytics covers the Promenade
The second method involves crawling Instagram and Twitter, for posts related to the Promenade, using relevant signifiers (e.g. #marinabay). An R script was written to retrieve over 5000 posts from Instagram, using Instagram’s API. The #marinabaysands (5836), #marinabaypromenade (186) and #marinabaywaterfrontpromenade (112) hashtags were used to identify posts that were related to our research. 7
A repository of tweets from 2015 were also used to supplement our dataset. The tweets were filtered using their geographical information. We analysed tweets that were posted within 500m of the Promenade (latitude: 1.280496, longitude: 103.8561567). In addition, we focused on tweets that were within 100m of the observation areas: the Lotus Pond (latitude: 1.2859531, longitude: 103.8591671), the Event Plaza (latitude: 1.2835728, longitude: 103.8584912) and the Sunbath Deck (latitude: 1.2815339, longitude: 103.8565567). In total, we analysed 6134 Instagram posts and 5952 Twitter posts. Our analysis of the data begins with passing every Instagram image to a classifier known as ResNet50 (from the Keras Python library). ResNet50 is an image classifier that employs the ResNet architecture, designed by He et. al. (2015) from Facebook AI Research (FAIR). The classifier was trained on ImageNet Large Scale Visual Recognition Challenge dataset, a compilation created by Stanford researchers, consisting of 1.2 million images across 1000 categories (Russakovsky et. al., 2015). When ResNet50 is supplied with an image, it returns a list of 1000 numbers, each of which represents the probability of the image being a certain category. For example, the last (1000th) number in the list represents the probability of the image being of toilet paper. This also means that all 1000 numbers should sum to 1. We then use the t-Distributed Stochastic Neighbor Embedding (tSNE) algorithm to compress the 1000-dimensional vectors into 2-dimensional vectors for visualization. Visually, we can observe several distinct clusters for common labels such as “fountain”, “lakeside”, “sunglasses” and “swimming attire”. For the Twitter posts, we use a pretrained GloVe model to generate sentence embeddings for the content of every post. GloVe is one of several word embedding models, which takes a textual input and returns a variable-sized vector that represents the abstract semantic meaning of the input (Pennington, 2014). 8
In our case, the GloVe model returned a 300-dimensional vector for each input tweet. We then perform k-means clustering on all of the vectors, using k=19 after trying several iterations. The t-SNE algorithm is then used to compress the 300-dimensional vectors (and the centroids of the clusters) into 2dimensions for visualization. By applying k-means to the sentence embeddings, we can detect clusters of similar topics amongst the thousands of Twitter posts, including check-in posts, food posts, emotional tweets and posts about events. Finally, we also looked at the time distribution for tweets across three different points of interest - the Lotus Pond, Event Plaza and Sunbath Deck. Specifically, we plotted the time distribution of the tweets across hours of the day, to see if there are any daily trends that might reveal activity patterns at the different locations. Analytics performed from secondary data sourced from social media platforms provides an additional display of space use and social interaction of the Promenade in the cyber realm that cannot be readily observed during the fieldwork, thus its findings used to complement as well as contrast the ethnographic results (Batty 2013, Boyd & Crawford, 2012).
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Photo 01. The Boardwalk after working hour
05. Findings 05.1 Boardwalk The boardwalk serves as a route to the rest of the CBD, with people are walking, jogging and cycling along the path. At lunch hour, a few office workers sat at the unshaded benches facing the waterfront, having lunch. But there is not more than a handful of people doing so, because it is very hot at this time of the day. At the benches shaded by trees, during office hours you can see office workers napping, or just finding their “alone space�.
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Photo 02 & 03. Napping Under the shades (left); Finding a personal space (right).
The “Rain Oculus�, an outdoor water feature in front of the Shoppes at Marina Bay Sands, looked very much like a sinkhole. Tourists would throw coins into it as if was a wishing well. At regular intervals, water would gush out, forming a whirlpool that pushes both the money and the water down into the basement of the Shoppes, where it continues to flow along the indoor water feature until it reaches the casino entrances. This aesthetics was designed with fengshui in mind, symbolizing the flow of money from willing patrons to the casino, although this symbolism is lost on those making their wishes at the Rain Oculus unless they have knowledge on Chinese geomancy. Ahead of the hungry sinkhole, a wide expanse of wooden flooring with a view onto the waterfront and the skyscrapers on the opposite shore. Unfortunately, the view was marred by a rather phallic structure erected in the middle of the bay. Nevertheless, or perhaps attracted by the phallus, tourists and visitors sauntered along the platform taking photos. Groups would walk to the edge, strike their poses and frozen smiles, before walking away to the next spot on their checklist. It was a languid game of musical chairs and merry-go-round. 11
Photo 04. Rain Oculus at the Shoppes at MBS (https://youtu.be/KFVyzz5Deqc)
The philosopher Heraclitus, famed for πάντα ῥεῖ (everything flows), uttered, “you cannot cross the same river twice”. Here, the impermanence of the flowing of water from Marina Reservoir into Singapore River via the bay is matched by the impermanence of the flowing tourists. In contrast to conserved, thus permanent, buildings along the old Singapore River, Marina Bay is a space of impermanence, transit and constant change. Yet, for a public space and tourist attraction, the boardwalk was startlingly empty on a cool Saturday afternoon. This might be partly attributable to the renovation works that blocked out segments of the waterfront. True to its nature of constant change, perpetual renewal are carried out in phases along the bay, as it characteristic of the city-state. Parts of the bay were boarded up by white wooden walls plastered with logos of "Marina Bay Sands Singapore”. Instead of the beautiful waterfront, visitors sitting on the benches could now feast their eyes on the hypnotic graffiti of capitalism and modernity. In this area of the boardwalk, benches that are supposed to face the waterfront are blocked by the temporary walls. This created unintended use functions, a case of seating on the same benches at the same location but 12
possibly for different reasons: previously, to sit at these benches would have given a panoramic view of the CBD skyline across the bay. Now, sitting there offers an illusion of privacy away from the open public space, due to the presence of walls on one side. Smokers gathering around a bin beside the boards. We observed sighs of relief on the facial expression of some of the employees from The Shoppes as they step out to take their smoke breaks. Here, at the impromptu smoking corner, they enjoy a moment of escape from the representation of courtesy and formality expected of their customer service roles, as they mingle with fellow comrades-in-arms before returning to the battlefront. The cleaning and maintenance crew – mostly South Asian laborers – appear at stipulated times of the day. Unlike the Shoppes' employees or the nearby office executives, these workers were never seen to rest or have lunch at the boardwalk. Their space for rest and recreation is hidden from the rest of the population.
Photo 05. Boardwalk
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Photo 06. Diagram of the average number of visitors at the Event Plaza.
05.2 Event Plaza The Event Plaza functions as a circulation space, a picturesque location to take photos or selfies along the waterfront. People typically take their photos and leave instead of linger, as it is very hot and glaringly bright during the day. The timber deck is collapsible. It forms the large boardwalk during the hot and humid day where people walk or cycle along it. At night, it turns into steps where crowds sit down for the fountain show. After all, it does not make sense to have people crowding around the front of The Shoppes during the day, potentially blocking access for people going inside for consumerist activities (in particular the purchase of luxury handbags and perfumes). The space is designed with the above considerations in mind. Our observations showed that visitor volumes surge in the evening, once the sun is down. 14
Photo 07. Event Plaza during Light and Water show. (Source: https://www.marinabaysands.com/singapore-visitors-guide/aroundmbs/light-and-sound-show.html)
Photo 08&09. Event Plaza during daytime; Event Plaza comes alive at night, with capacity to accommodate visitors up to 3000 Pax. (Below. Source: https://www.ma rinabaysands.c om/singaporevisitorsguide/aroundmbs/light-andsoundshow.html)
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Photo 10. Diagram of the average number of visitors at The Lotus Pond.
05.3 Lotus Pond The traffic is visibly denser at the lotus pond outside the ArtScience Museum, where people sat at the edge of the pond and taking selfies with the flora and the skyline of the CBD. The shade, offered by the architecture of the museum, appears to impose a virtual boundary on the sitting area. Within these boundaries, clusters of people sit at surprisingly regular intervals - an unspoken acknowledgement of personal space. Few visitors venture out of the shade and onto the unshaded side of the lotus pond on a hot and humid day, perhaps yearning for more breathing room. Both visitors and employees appear to treat the lotus pond as a resting space, some taking the occasional photo but mostly sitting and engaging in small talk. Where there is a bin and a corner, smokers will gravitate towards it for a puff. The most common activities at the Lotus Pond is taking selfies and wefies, sleeping and as a sitting place for social gathering. 16
Photo 11-15. Selfie in actions at the Lotus Pond
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Photo 16. Diagram of the average number of visitors at the Sunbath Deck.
05.4 Sunbath Deck At the sunbathing deck, the sunbathing chairs are too heavy to move and deceptively uncomfortable. Bits of broken wood threaten to splinter the unwary sitter. It is probably more accurate to call these props rather than chairs. Adjacent chairs are positioned slightly too far for comfortable conversation. But the alternative of two people sitting on one chair is equally undesirable. The angle of the chair inexorably causes one person to slide into the other, perhaps palatable for those with an utter disregard for personal space. Corresponding to the climate, the sunbath deck sees increase use volumes around dusk. 18
Figure 05. Result of the postings on Instagram.
05.5 Instagram
When we retrieve posts using the #marinabaysands hashtag, many of the photos were not taken at the Marina Bay Waterfront site. This might imply that the waterfront is not a very 'Instagram-worthy' site. Photos of iconic structures such as the Marina Bay Sands, the LV Building and the Art Science museum are commonly taken from far rather than up close on site. Our selection criteria (#marinabaysands) might also be too general, resulting in many images that are of Marina Bay Waterfront but not at Marina Bay Waterfront. A preferable approach would have been to make use of the location information for each post. Unfortunately, that is rarely available in today's privacy climate. Instead, we also included more specific hashtags of #marinabaypromenade and #marinabaywaterfrontpromenade. While these hashtags yielded significantly fewer posts, many of these posts were evidently taken in close proximity of the waterfront area. 19
Main clusters of images detected by the ResNet50 classifier includes images associated with the waterfront, which are frequently labelled “fountain”, “lakeside”, “dock”, “pier” and “breakwater”. Another significant group consists of the “selfie” cluster, which includes images with people as the subject, such as pictures that are labelled “swimming attire” and “sunglasses”. These photos are mostly taken at the Infinity Pool on top of Marina Bay Sands, with a smaller proportion taken at the waterfront area, near the timber deck. We might also infer that many of the selfie photos were taken by tourists rather than locals. By visually inspecting images labelled 'swimming attire' or 'sunglasses', we see that many of the individuals featured in the images appear to be foreigners. It is also interesting that many of the scenic photos appear to be taken from similar angles and locations. For example, photos of the Merlion are always taken such that the statue is spouting water to the left. During a later site visit, we found that this was because there was a platform to the left of the Merlion that facilitated such photos, an interesting case of digital activities reflecting physical spaces. Relying on Instagram posts as a single source of data, one might infer that the activities at Marina Bay Waterfront essentially consists of posing at the timber deck and Infinity Pool, as well as taking photos of the skyline from the Merlion Park. Interestingly, we did find that there was a considerable tourist population at the waterfront posing for photos and a massive crowd at the Merlion Park. However, such conclusions neglect other populations at the waterfront, who might have a more negligible social media presence. While unrelated to our study, images of food also feature heavily amongst the Instagram posts, which can be attributed to the nature of Instagram and social media in general. 20
Figure 06. Result of the postings on Twitter.
05.6 Twitter As mentioned earlier, the collected tweets mainly revolve around check-in posts, food posts, emotional tweets and posts about events. Check-in posts constitute a majority of the tweets, which unfortunately reveals rather little about the activities that the visitors engage in. More interesting are the event tweets, which were mainly about the light and water show Spectra, exhibits at the ArtScience Museum, and performances at the Marina Bay Sands Theatre. These give us a clue to popular activities at the waterfront, other than shopping at The Shoppes and taking photos for Instagram. In particular, the presence of tweets about Spectra also correspond to our onsite observations of a large audience watching the light and water show.
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The clustering also revealed a significant number of foreign language tweets, which hint at the foreign tourist population at the waterfront. Featured languages include Bahasa (a majority), Japanese, Korean, Thai and Arabic. It is important to note that Germanic (e.g. German, Dutch) and Romance (e.g. French, Italian) languages might not be obviously clustered due to their similarity to English and the nature of the algorithms used. Using the timestamps of the tweets, we also plotted the distribution of tweets across hours of the day at three areas of interest. We found that the Lotus Pond has peak activity at 6pm, the Timber Deck has peak activity at 8pm and 10pm, while the Sunbath Deck has peak activity at 3pm and 6pm. This approximately agrees with our field notes. Specifically, we observe little activity in the morning and noon periods, which we attribute to the hot and humid weather. This is followed by increasing activity in the late afternoon, especially at the Lotus Pond and Sunbath Deck. Finally, a crowd gathers at the Timber Deck at night to watch the light and water show, which occurs daily at 8pm and 9pm.
Figure 07. Diagram shows the average number of visitors at the location of observations.
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06. Discussion 06.1Photographic use of space: Icons Far and Near The architectural designs of the space could be categorized into “near” and “far” for the purposes of photogenic sceneries or selfies. Near
Far
Lotus pond at ArtScience Museum The Shoppes Water features at The Shoppes Crystal Pavilions: North (LV Store) & South (former Avalon nightclub; undergoing construction works) Red-dot design museum
ArtScience Museum MBS hotel towers and skypark MBS complex in entirety CBD skyline from Lotus pond and Event Plaza
Interiors of MBS complex
Marina Bay financial district skyline from Sunbathing deck Marina Bay Centre skyline from Lotus pond
The "far" icons are physically massive and requires the aspiring model to take a photo from far away. These include the hotel towers and skypark, the ArtScience Museum, and the complex in its entirety. A quick search for #marinabaysands revealed hundreds of such photos, which were obviously taken from a distance. These photos were often taken from the Merlion Park at the opposite bank. "Near" icons are much smaller, allowing budding models to strike up poses right next to the structures, often allowing for physical contact. Such icons include the lotus pond under the ArtScience Museum and the Merlion. For a "near" icon to capitalize on its photogenic qualities, platforms nearby should physically encourage visitors to get up close and personal. Examples include the sitting space at the edge of the lotus pond and the extended 23
platform next to the Merlion. In contrast, "far" icons would obviously require platforms or photo-spots that are far away, such that the full glory of the structures can be captured. Hence, the Merlion Park serves both the "near" Merlion and the "far" Marina Bay Sands, attracting crowds of tourists in rain and shine. The nature of the icon might also explain the nature of the space. As such, there are fewer tourists taking selfies outside the Shoppes, a "far" icon, because the mall looks just like any other mall when seen up close. The sparse empty space outside the Shoppes transits to a more crowded area near the ArtScience Museum, with more selfies at the lotus pond, a "near" icon.
Photo 17. Photo-spots platform next to the Merlion.
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Figure 08. Diagram shows the average total number of visitors across different time and location of observations through Fieldworks.
06.2 Space Popularity On site, the Lotus Pond is the most popular day time space, where the traffic moves towards Event Plaza in the evening. Interestingly, popularity on the cyberspace differs from that on the physical space. The proportions of tweets made from each area is relatively stable throughout the day. On cyberspace, Event Plaza is most popular (N=3439, 78.2%) followed by Lotus Pond (N=824, 18.7%) and Sunbath Deck (N=137, 3.1%). 25
Figure 09. Diagram shows the average total number of visitors across different time and location of observations through Tweets.
The favorite location for selfies is the Lotus Pond during the day and the event plaza in the evening. The natural lighting and design space at the Lotus Pond make for great day time photos. At the Event Plaza, the night time lighting of the CBD skyline and the light show creates a good backdrop for photo taking, although not as popular as the Lotus Pond. Universally recurring activities across the sub-areas are taking photos (especially selfies), sitting, eating, and sleeping. Smoking is more common around corners, at boardwalk and lotus pond, preferably under shades where available. But the lack of shelter, whether rain or shine, will be hard to deter a smoker from the need for a puff.
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Sleeping is done everywhere, as long as the person finds it comfortable to sleep! And the best part is along the benches at the edge of Lotus Pond, where the reflective sculpture from world famous artist Anish Kapoor creates a tranquil meditative moment in the midst of crowded intersection. Another universal favorite is food: the act of eating on site, and social media posts on food transcends nationalities and spaces.
Figure 10. Table of Activities: Physical vs Cyber.
Photo 18. Anish Kapoor’s Sky Mirror sculpture. 2010.
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07. Limitations The limitations of using social media as a source of data originate mainly from its primary user base of tech-savvy individuals who are typically of a younger demographic. This means that the data is only representative of a rather narrow demographic segment, neglecting other voices such as the elderly who might be unwilling or unable to participate in such platforms. In addition, social media tends to promote narcissistic activity, where individuals are prone to authoring “show-off” posts to impress his or her followers. This has the effect of encouraging posts consisting of delicious food, extravagant activities and beautiful scenery. In addition, posts are also frequently upbeat and positive, often exaggeratedly so. This obviously skews any conclusion an analyst might have. The clueless analyst might infer that, no matter the location and time, visitors are often happy people whose main activities revolve around eating delicious food and looking at beautiful scenery. Nevertheless, social media represents an important source of data, if only for the sheer amount of content that is available. In our analysis, we have also noted several digital trends that had physical counterparts.
Most importantly, there is a need to compare and contrast digital and physical methods, as well as quantitative and qualitative ones, to derive a more wholesome perspective of a public space. Social media is a promising source of data, but we have to be cognizant of its in-built bias. A clear source of biases is the recent proliferation of ‘fake news’, which has led to tremendous repercussions around the world (Nugent 2018, Allcott 2017). These biases are often target-based, depending on the intended audiences across the different platforms (Ruths & Pfeffer 2014). Given the potential biases demarcated by differences, whether perceived or actual, it may be difficult to draw conclusions that are representative of the general population. 28
08. Reflections One of the main challenges was the difficulty in filtering out Instagram or Twitter posts that were out of the scope of our study. Ideally, if geolocation information was available for every post, we could simply filter the posts by location. However, in light of the recent data privacy legislations, most of the posts no longer contain geolocation data. We resolved this problem in two ways. First, we made use of Twitter data from 2015, provided by Prof. Ate Poorthuis. Tweets from back then contained geolocation data and we could then filter out tweets that were not posted at the waterfront. Second, for our Instagram dataset, we made use of appropriate hashtags to identify posts that were relevant to our study. Initially, we used the #marinabaysands hashtag. However, we quickly realized that many of the posts were not taken in the vicinity of the waterfront area, with some posts even extending to East Coast Park or Gardens by the Bay. We then switched to #marinabaypromenade and #marinabaywaterfrontpromenade hashtags that returned results that appeared to be taken in close proximity to the waterfront. However, we probably missed out many posts that were taken at the waterfront but not tagged with the aforementioned hashtags. Another challenge was in abstracting the large dataset in an appropriate fashion for us to retrieve suitable insights. In the previous sections, we mentioned making use of the ResNet50, GloVe and k-means algorithms to cluster the data. However, the use of these algorithms could be argued as arbitrary. We could have changed the implementation details for these algorithms or even change the entire algorithm and use other alternatives. For example, the ResNet50 model is just one of dozens of models that are available. We mainly chose it out of convenience and another model might 29
very well give us different results. In the case of the k-means algorithm, a random initialization meant that every run of the algorithm would give a subtly different result. The number of clusters was also chosen quite arbitrarily, after trying out several iterations. In short, there is a significant degree of haphazardness that constrains the objectivity of our results. Rather than uncovering the truth, we are uncovering a truth, depending on what method we use and how we use the method.
As for the Fieldwork, it is challenging to navigate the large site of observation, which stretches almost a kilometre long. Weather conditions such as extreme heat during day time or sudden rain in most cases became an obstacle, although in an rare occasion may lead to an interesting finding, for instance we discovered popular seating area during rain. For future research improvement, to complement fieldwork findings, we may need to conduct interview with visitors on site. This may give us more clarity on their perception and expectation on what determine a good public urban space. The combination of data analytics, fieldwork observation with interviews will build up a very solid methodology to influence the urban designer and planner, and policy maker in defining the public urban space. Within the context of Singapore urban development which is constrained by the scarcity of land, this type of research will benefits various stakeholder in the city and urban development. We are very much inspired by our collaborative works, and look forward to working with the larger group of researchers and practitioners to tackle the real contentious urban development issues.
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09. Conclusion In this study, we showed that the use of and social interactions in both the physical and cyber spaces are very much influenced by the urban design. The built environment, and increasingly, the digital media environment, shapes how and what people do at a location, and the social interactions and meaning making of their actions. This study also demonstrated the power of the shift from Urban Studies to
Urban Science: more man-hours were required to conduct fieldwork confined to a section of the promenade (the Boardwalk) as compared to less man-hours required to perform data analytics on the entire promenade1. The ubiquitous use of social media has arguably altered spatial use and its associated social interactions, but a replacement of spaces, but an amalgamation. In this study we made an early attempt to integrate the merits of both “classical” and “data”. We hope this can contribute to the future of urban craft-making. Thus, we posit that combining data science methods with Whyte’s approach – often seen as canonical – opens up new, exciting possibilities in socio-urban literature that provides a timely update to a classic masterpiece for a more comprehensive research relevant to contemporary society.
1 In view of our limited site coverage, a further study could expand the physical area to increase the number of meaning comparisons with the findings derived from the analytics conducted.
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Appendix
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Video Link: Boardwalk https://youtu.be/8cLpZUjWxGc
Video Link: Event Plaza https://youtu.be/P9jffMSY3RU
Video Link: Lotus Pond https://youtu.be/k5F-vesZNdw
Video Link: Sunbath Deck https://youtu.be/_rzgFt5E-9Y
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