City Flow: Prototype Exploration for Visualizing Urban Traffic Conversations

Wu, Junjie; Fu, Zhiyong; Liu, Zhiyuan; Pan, Jiajia; Huang, Long; Lin, Xu; He, Haoqing; Chen, Xinxiong; Tang, Jiayu

doi:10.1109/socialcom-passat.2012.40

Cited by 4 publications

(5 citation statements)

References 8 publications

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“…For instance, the expansion of urban centers require understanding the accessibility and commuting efficiency of people to transportation and job opportunities, as explored by [79,80,81]. Urban traffic conversations extracted from geo-referenced social media data can be further exploited, as in [91], to generate insights on the conditions of a transportation network and people’s commuting habits. Further studies could assess the potential of interactive 3D visualization of urban mobility data, as it has been addressed by a few studies [31,54,74,75].…”

Section: Discussionmentioning

confidence: 99%

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Visualization of Urban Mobility Data from Intelligent Transportation Systems

Sobral

Dias

Borges

2019

Sensors

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Intelligent Transportation Systems are an important enabler for the smart cities paradigm. Currently, such systems generate massive amounts of granular data that can be analyzed to better understand people’s dynamics. To address the multivariate nature of spatiotemporal urban mobility data, researchers and practitioners have developed an extensive body of research and interactive visualization tools. Data visualization provides multiple perspectives on data and supports the analytical tasks of domain experts. This article surveys related studies to analyze which topics of urban mobility were addressed and their related phenomena, and to identify the adopted visualization techniques and sensors data types. We highlight research opportunities based on our findings.

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Section: Discussionmentioning

confidence: 99%

“…Wu et al proposed a prototypical visualization tool for exploring conversations about traffic using microblogging data [91], with focus on sentiment analysis and trending topics. The system provides abstract visualization techniques mostly based on variations of word clouds.…”

Section: Literature Reviewmentioning

confidence: 99%

Visualization of Urban Mobility Data from Intelligent Transportation Systems

Sobral

Dias

Borges

2019

Sensors

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“…The most popular choice by far is Colour , used by 89% of techniques. Most techniques that focus on polarity values use green for positive and red for negative polarity [WS08, TPTV16], although several techniques reverse this colour map to use green/blue as a cold hue corresponding to negative polarity, and orange/red for positive polarity [WFL*12, WFL*13, CAHF14, CFKA14, HC14, HC16, YWC*16]. The techniques related to emotions or affect categories other than positive/neutral/negative use either an ordinal set of colours representing categories [KR11 ZGWZ14, EAGA*16] or interpolate the colours based on the corresponding dimensional model [Alm13, WSK*15].…”

Section: Sentiment Visualization Techniquesmentioning

confidence: 99%

“…Wu et al . [WFL*12] use a cartogram for their system City Flow to represent sentiment of Weibo posts originating from specific cities. The sizes of nodes represented by squares are calculated similarly to a regular tree map, but the layout takes the geographical positions of cities into account.…”

Section: Sentiment Visualization Techniquesmentioning

confidence: 99%

The State of the Art in Sentiment Visualization

Kucher

Paradis

Kerren

2017

Computer Graphics Forum

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“…In the first version of visualization prototype we present ten top topics in each city by random, which is elaborated in another paper City Flow: Prototype Exploration for Visualizing Urban Traffic Conversations [2]. By observing that online prototype we found a variety of topics talked by people about urban traffic.…”

Section: Related Topicsmentioning

confidence: 99%

Creating reflections in public emotion visualization

Liu

et al. 2013

Proceedings of the 9th ACM Conference on Creativity &Amp; Cognition

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The paper presents a visualization prototype that tackles the issue of public emotion. It emphasizes the exploration process in the aim of creating reflections for the viewer to observe the whole social context as well as individual perspectives. Urban traffic conversation on SNS (Social Networking Site) is our current interest. The prototype we present is made on real post streams captured from Chinese most popular microblog Sina Weibo. After experimenting on two online prototypes we determine a visualizing flow to lead the viewer going through the insights from macro to micro view in three interaction frameworks: City Sentiment, Related Topics, and Post Content. Through showing the visualizing flow with interaction mode, data analysis, and prototype construction, the paper ends with discussing about design considerations in creating reflections on public traffic emotion in visualization prototype.

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City Flow: Prototype Exploration for Visualizing Urban Traffic Conversations

Cited by 4 publications

References 8 publications

Visualization of Urban Mobility Data from Intelligent Transportation Systems

Visualization of Urban Mobility Data from Intelligent Transportation Systems

The State of the Art in Sentiment Visualization

Creating reflections in public emotion visualization

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