Social media analysis of car parking behavior using similarity based clustering

Arhab, Nabil; Oussalah, Mourad; Saroar, Jahan, Md

doi:10.1186/s40537-022-00627-x

Cited by 7 publications

(3 citation statements)

References 70 publications

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“…Using clustering methods, spatio-temporal parking patterns can also be found in other cities such as Seattle [50], Munich [41], and Beijing [51]. Even multiple parking behaviors around the globe can be identified through social media [52]. In general, these studies' results are consistent with our results.…”

Section: Dimension Reduction and Clusteringsupporting

confidence: 89%

Clustering Analysis of the Spatio-Temporal On-Street Parking Occupancy Data: A Case Study in Hong Kong

2022

Sustainability

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Parking plays an essential role in urban mobility systems across the globe, especially in metropolises. Hong Kong is a global financial center, international shipping hub, fast-growing tourism city, and major aviation hub, and it thus has a high demand for parking. As one of the initiatives for smart city development, the Hong Kong government has already taken action to install new on-street parking meters and release real-time parking occupancy information to the public. The data have been released for months, yet, to the best of our knowledge, there has been no study analyzing the data and identifying their unique characteristics for Hong Kong. In view of this, we examined the spatio-temporal patterns of on-street parking in Hong Kong using the data from the new meters. We integrate the t-SNE and k-means methods to simultaneously visualize and cluster the parking occupancy data. We found that the average on-street parking occupancy in Hong Kong is over 80% throughout the day, and three parking patterns are consistently identified by direct data visualization and clustering results. Additionally, the parking patterns in Hong Kong can be explained using land-use factors. Overall, this study can help the government better understand the unique characteristics of on-street parking and develop smart management strategies for Hong Kong.

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Section: Dimension Reduction and Clusteringsupporting

confidence: 89%

Clustering Analysis of the Spatio-Temporal On-Street Parking Occupancy Data: A Case Study in Hong Kong

2022

Sustainability

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“…These methods aim to detect the underlying structure in the network, identify nodes with strong connectivity, and assign them to different communities or groups. Some wellknown community discovery algorithms, such as Louvain algorithm [18], GN algorithm [19] and modular maximization [20]and so on, have been widely used in social networks, news networks and other fields to help reveal community structures and social relationships.…”

Section: Related Workmentioning

confidence: 99%

POS‐HC: A Part‐of‐Speech Hierarchical Clustering Approach for Normative Texts Partition

Li,

Liu,

Deng

et al. 2024

Preprint

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Chinese texts often feature a substantial volume of normative content, and their analysis has increasingly become a focal point in recent semantic analysis endeavors. Enhancing the effectiveness of text classification and clustering is pivotal in unveiling the intricate semantics within extensive textual data. Empirical research within the realm of computational social science has underscored the need for improved explanatory power when it comes to general text clustering methods applied to normative texts. This study introduces an innovative hierarchical clustering method that incorporates part-of-speech (POS) features and pioneers a novel semantic network model. It achieves this by amalgamating a POS-based feature weight calculation method with hierarchical clustering techniques. To assess its efficacy, the method is rigorously evaluated across three diverse text datasets, encompassing normative reports, news articles, and social media content. The experimental results unequivocally demonstrate the superior performance of the POS-HC method, surpassing the traditional TF and TF-IDF feature extraction methods in terms of clustering accuracy, and surpassing some existing clustering methods. Furthermore, its classification effectiveness exhibits notable advantages, particularly in the semantic classification of normative texts.

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“…The problems of parking behavior of residents have been studied by many researchers such as Arhab [11], Herath [12] and Kang [13]. For example, Elisabeth Fokker et al [14] investigated the short-term and long-term impact of a new subway line on parking behavior of residents and they found that in the short term, more commuters tend to park in the city center close to the stations of this public transport line.…”

Section: Literature Reviewmentioning

confidence: 99%

Bus users’ behavior in using parking services and their expectations for the development of parking service quality at bus stations in Hanoi, Vietnam

Phuong,

Kojima,

Kubota

2023

IOP Conf. Ser.: Mater. Sci. Eng.

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Transportation Demand Management (TDM) has been introduced in Vietnam to keep the balance between the limited supply of road network, and the increase of private vehicles and Park & Ride (P&R) is one of TDM’s measures focused on the transition from private to public transport at stations. This research investigated the current situation of parking areas and bus users’ behavior in 4 main stations in Hanoi, Vietnam. Furthermore, bus users were asked in the assumption case that if they cannot use the bus, how much they will pay for the travel cost and time in that case compared to the actual case when they use the bus. The results have found that many people have accepted to travel in a longer time to save travel costs. This research also identified the factors which influence on using P&R services in station of bus users. Based on the Binary logistic regression model, the “Income” factor is one of the significant characteristics of bus users on selection use or not use of P&R services at the bus station. Finally, bus users’ expectations on the current situation of the parking services at stations gave some suggestions to improve the P&R services in bus stations in Hanoi.

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Social media analysis of car parking behavior using similarity based clustering

Cited by 7 publications

References 70 publications

Clustering Analysis of the Spatio-Temporal On-Street Parking Occupancy Data: A Case Study in Hong Kong

Clustering Analysis of the Spatio-Temporal On-Street Parking Occupancy Data: A Case Study in Hong Kong

POS‐HC: A Part‐of‐Speech Hierarchical Clustering Approach for Normative Texts Partition

Bus users’ behavior in using parking services and their expectations for the development of parking service quality at bus stations in Hanoi, Vietnam

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