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Social media as passive geo-participation in transportation planning-how effective are topic modeling&sentiment analysis in comparison with citizen surveys?

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Geo-Spatial Information Science 2020年第4期23卷 275-292页

作者： oliver lock Christopher Pettit City Futures Research Centre Faculty of Built EnvironmentUniversity of New South Wales(UNSW)SydneyAustralia Expanded Perception and Interaction Centre(Epicentre) Faculty of Art&DesignUniversity of New South Wales(UNSW)SydneyAustralia

We live in an era of rapid urbanization as many cities are experiencing an unprecedented rate of population growth and *** transport is playing an increasingly important role in urban mobility with a need to move people and goods efficiently around the *** such pressures on existing public transportation systems,this paper investigates the opportunities to use social media to more effectively engage with citizens and customers using such *** research forms a case study of the use of passively collected forms of big data in cities-focusing on Sydney,***,it examines social media data(Tweets)related to public transport ***,it joins this to longitudinal big data-delay information continuously broadcast by the network over a year,thus forming hundreds of millions of data ***,tones,and sentiment are modeled using machine learning and Natural Language Processing(NLP)*** resulting data,and models,are compared to opinions derived from a citizen survey among *** validity of such data and models versus the intentions of users,in the context of systems that monitor and improve transport performance,are *** such,key recommendations for developing Smart Cities were formed in an applied research context based on these data and techniques.

关键词： Social media smart cities public participation urban sensing transport planning natural language processing machine learning big data

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The visual analytics of big,open public transport data-a framework and pipeline for monitoring system performance in Greater Sydney

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Big Earth Data 2021年第1期5卷 134-159页

作者： oliver lock Tomasz Bednarz Christopher Pettit City Analytics Lab Faculty of Built EnvironmentUniversity of New South WalesSydneyAustralia Expanded Perception and Interaction Centre Faculty of Art&DesignUniversity of New South WalesSydneyAustralia

Many cities,countries and transport operators around the world are striving to design intelligent transport *** systems capture the value of multisource and multiform data related to the functionality and use of transportation infrastructure to better support human mobility,interests,economic activity and *** aim to provide services that can enable transportation customers and managers to be better informed and make safer and more efficient use of *** developing principles,guidelines,methods and tools to enable synergistic work between humans and computer-generated information,the science of visual analytics continues to expand our understanding of data through effective and interactive visual *** this paper,we describe an application of visual analytics related to the study of movement and transportation *** application documents the use of rapid,2D and 3D web visualisation and data analytics libraries and explores their potential added value to the analysis of big public transport performance data.A novel approach to displaying such data through a generalisable framework visualisation system is *** framework recalls over a year’sworth of public transport performance data at a highly granular level in a fast,interactive browser-based *** Sydney,Australia forms a case study to highlight potential uses of the visualisation of such large,passively-collected data sets as an applied research *** this paper,we argue that such highly visual systems can add data-driven rigour to service planning and longer-term transport ***,they enable the sharing of quality of service statistics with various stakeholders and citizens and can showcase improvements in services before and after policy *** paper concludes by making recommendations on the value of this approach in embedding these or similar web-based systems in transport planning practice,performance

关键词： WebGL visual analytics public transportation transport performance visualisation open data big data

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