The rise of big data on urban studies and planning practices in China: Review and open research issues

Jin, Hao; Zhu, Jiaqian; Zhong, Rui

doi:10.1016/j.jum.2015.11.002

Cited by 105 publications

(53 citation statements)

References 37 publications

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“…While these individuals are geolocated, the spatial projection of the community is related to the abovementioned "interaction fields". Despite their limits, these new methods and data have turned out to be effective tools for analysis, visualisation and urban planning [see for example Sagl et al, 2014;Hao et al, 2015].…”

Section: Figure 1 Simplified Representation Of the Detection Of Groumentioning

confidence: 99%

Cartography of interaction fields in and around Brussels: commuting, moves and telephone calls

Adam¹,

Delvenne²,

Thomas³

2017

brussels

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Section: Figure 1 Simplified Representation Of the Detection Of Groumentioning

confidence: 99%

Cartography of interaction fields in and around Brussels: commuting, moves and telephone calls

Adam¹,

Delvenne²,

Thomas³

2017

brussels

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“…Big data is beneficial for citizens as well as policymakers as it provides alternative visions and decision-making patterns in everyday life of the city (Kitchin, 2014). The big data can be used to increase people's indirect participation in urban planning, but it requires numerous further studies as the field of study is still very young and emerging (Crampton et al, 2013;Hao, Zhu, & Zhong, 2015). The interactions through social media should not be merely considered as a way of reading the network but an inherited part of its reality.…”

Section: Reading Urban Space Through Big Datamentioning

confidence: 99%

Exploring Patterns of Socio-spatial Interaction in the Public Spaces of City through Big Data.

Iranmanesh

Atun

2017

Proceedings 24th ISUF 2017 - City and Territory in the Globalization Age

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Research on socio-spatial aspect of cities has never been so vibrant and exciting. The form of urban life is changing and evolving with new advancements in communication and technology. Digital communication and social media has reshaped the way people as the actors of society interact with each other and with the network of city. New social networks and widespread of mobile devises can be used to create and reinforce existing social ties. Mobile devises also change the role of citizens from consumers into producers of data; they are the new reporters, photographers, videographers of everyday life. This production creates large quantities of data known as the “Big Data”. Big data has opened up many doors for researchers to investigate new aspects of cities. This paper aims to explore how people access urban public spaces through social media by taking the parameter of distance and physical proximity into account. We tried to investigate if different levels of accessibility effects the way people interact with space through social media. Through this process the study explored different socio-spatial patterns in the city that are being affected by social media. The research data was collect in two layers of Nicosia in Northern Cyprus: first, the geo-tagged social media data was collected from the target group, and it was located on the map. Twitter as a microblogging medium was selected for data collection due to its public nature, geo-tagged abilities, and manageable short content. Second, degrees of accessibility in local and global scale were calculated using Space Syntax. The data was analyzed using regression analysis, scatter plot, and outlier detention. The result shows various patterns in correlation of interactions between society and space; it illustrates the importance of exploring the outliers when reading big data on the city. The result shows clear importance of local accessibility even when social media is the effective variable.

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“…Als die individuen gegeolokaliseerd zijn, lijkt de projectie van de community in de ruimte op de hoger genoemde "interactiegebieden". Ondanks hun beperkingen is al gebleken dat deze nieuwe methodes en data effectieve instrumenten zijn voor stadsanalyse, -visualisatie en -planning [zie bijvoorbeeld Sagl et al, 2014;Hao et al, 2015]. Op basis van gegevens uit de laatste volkstelling (verhuizingen en woonwerkverplaatsingen) en de telefonische contacten wil dit artikel tonen welke plaatsen nauw verbonden zijn met elkaar in en rond Brussel en zo de "interactiebassins" in kaart brengen aan de hand van een methode voor de detectie van communities (Louvain method -zie punt 2).…”

Section: Note De L'auteurunclassified

Cartografie van de interactiegebieden in en rond Brussel: pendelverkeer, verhuizingen en telefoongesprekken

Adam¹,

Delvenne²,

Thomas³

2017

brussels

View full text Add to dashboard Cite

The rise of big data on urban studies and planning practices in China: Review and open research issues

Cited by 105 publications

References 37 publications

Cartography of interaction fields in and around Brussels: commuting, moves and telephone calls

Cartography of interaction fields in and around Brussels: commuting, moves and telephone calls

Exploring Patterns of Socio-spatial Interaction in the Public Spaces of City through Big Data.

Cartografie van de interactiegebieden in en rond Brussel: pendelverkeer, verhuizingen en telefoongesprekken

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