A framework for involving the young generation in transportation planning using social media and crowd sourcing

Anik, Asif Hasan; Sadeek, Soumik Nafis; Hossain, Moinul; Kabir, Shafquat

doi:10.1016/j.tranpol.2020.06.006

Cited by 14 publications

(11 citation statements)

References 15 publications

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“…The general public are the primary users of the transportation services of an area. Their opinions and concerns may help us to better understand the challenges and opportunities of the transport system ( 5 ). In addition, the implications of lockdown for people’s mobility and participation in activities can be more clearly understood.…”

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confidence: 99%

Impacts of COVID-19 on Transport Modes and Mobility Behavior: Analysis of Public Discourse in Twitter

Habib

Anik

2021

Transportation Research Record: Journal of the Transportation R

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This study proposes a framework to analyze public discourse in Twitter to understand the impacts of COVID-19 on transport modes and mobility behavior. It also identifies reopening challenges and potential reopening strategies that are discussed by the public. First, the study collects 15,776 tweets that relate to personal opinions on transportation services posted between May 15 and June 15, 2020. Next, it applies text mining and topic modeling techniques to the tweets to determine the prominent themes, terms, and topics in those discussions to understand public feelings, behavior, and broader sentiments about the changes brought about by COVID-19 on transportation systems. Results reveal that people are avoiding public transport and shifting to using private car, bicycle, or walking. Bicycle sales have increased remarkably but car sales have declined. Cycling and walking, telecommuting, and online schools are identified as possible solutions to COVID-19 mobility problems and to reduce car usage with an aim to tackle traffic congestion in the post-pandemic world. People appreciated government decisions for funding allocation to public transport, and asked for the reshaping, restoring, and safe reopening of transit systems. Protecting transit workers, riders, shop customers and staff, and office employees is identified as a crucial reopening challenge, whereas mask wearing, phased reopening, and social distancing are proposed as effective reopening strategies. This framework can be used as a tool by decision makers to enable a holistic understanding of public opinions on transportation services during COVID-19 and formulate policies for a safe reopening.

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confidence: 99%

Impacts of COVID-19 on Transport Modes and Mobility Behavior: Analysis of Public Discourse in Twitter

Habib

Anik

2021

Transportation Research Record: Journal of the Transportation R

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“…Pattern 1 Conceptual topics Green buildings [22], transportation planning [14], climate change [26], low-carbon city [41] Pattern 2 Event-based topics…”

Section: Pattern Name Examplesmentioning

confidence: 99%

“…In recent years, social media, such as Twitter, Facebook and Weibo, has been cited as an important tool for scholars investigating a variety of fields, including social sciences [8], communication [6,7], politics [9,10], education [11,12], medical science [13], transportation [14] and disaster management [15,16]. As compared to traditional data collection channels, such as surveys or questionnaires, social media can yield a better understanding of the public perceptions, decrease time and commercial costs in the data collection process, and display a greater variety and geographic distribution in the data [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

A Normalized Rich-Club Connectivity-Based Strategy for Keyword Selection in Social Media Analysis

et al. 2022

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In this paper, we present a study on keyword selection behavior in social media analysis that is focused on particular topics, and propose a new effective strategy that considers the co-occurrence relationships between keywords and uses graph-based techniques. In particular, we used the normalized rich-club connectivity considering the weighted degree, closeness centrality, betweenness centrality and PageRank values to measure a subgroup of highly connected “rich keywords” in a keyword co-occurrence network. Community detection is subsequently applied to identify several keyword combinations that are able to accurately and comprehensively represent the researched topic. The empirical results based on four topics and comparing four existing models confirm the performance of our proposed strategy in promoting the quantity and ensuing the quality of data related to particular topics collected from social media. Overall, our findings are expected to offer useful guidelines on how to select keywords for social media-based studies and thus further increase the reliability and validity of their respective conclusions.

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“…To make up for these limitations, a more efficient collection method is needed. Fortunately, the strong growth of textual data volume and advancements within natural language processing (NLP) provides a new way to solve this problem [9][10][11]. Public opinion analysis has emerged to meet this need.…”

Section: Introductionmentioning

confidence: 99%

Extraction Method and Integration Framework for Perception Features of Public Opinion in Transportation

2020

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To better facilitate government management and planning based on public opinion, it is essential to propose a method for extracting public opinion perception features in consideration of an integrated framework, which aims at industry monitoring and decision-making. Based on fundamental characteristics of ordinary traffic incidents, this paper develops a perception features system of public opinion consisting of four modules, where the construction methods have been elaborated. First, mining thematic features is realized via the similarity calculation of text vector. Second, based on summarized Chinese expression patterns, time extraction rules, and a five-layer tree-like spatial feature thesaurus are established to extract spatiotemporal features. Third, the modeling of the emotional features is achieved by a dictionary-based analysis model. Fourth, the evolutional features are extracted by the Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH). In view of the attributes of each module, an integrated framework is built to determine the collaboration relationship of feature indicators. Finally, a case study of Shenzhen public transport has been performed to illustrate the application of proposed methods. Results show that the strong odor in electric buses and a rumor that electric buses have great radiation are two main causes of the decrease in passenger satisfaction in the first quarter of 2017. In contrast, adding new bus lines, increasing service frequency, and guaranteeing the bus-lane right will improve passenger satisfaction, which is basically consistent with the official report. It should be noticed that the developed framework has been validated in the case study of passenger satisfaction analysis, while it can be extensively replicated in other fields. Furthermore, it is important for stakeholders to grasp the public perception of transportation services, in order to enhance public participation in transportation management and decision-making.

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A framework for involving the young generation in transportation planning using social media and crowd sourcing

Cited by 14 publications

References 15 publications

Impacts of COVID-19 on Transport Modes and Mobility Behavior: Analysis of Public Discourse in Twitter

Impacts of COVID-19 on Transport Modes and Mobility Behavior: Analysis of Public Discourse in Twitter

A Normalized Rich-Club Connectivity-Based Strategy for Keyword Selection in Social Media Analysis

Extraction Method and Integration Framework for Perception Features of Public Opinion in Transportation

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