Urban Emotions

//Urban Emotions
Urban Emotions

 

Extracting Contextual Emotion Information for Spatial Planning
Real-time “People as Sensors and Social Media”

 

 


 

M
Methods

The spatial and social structures of a city such as buildings, the transport infrastructure, parks as well as the dynamic nature of human activities and its underlying processes can trigger different collective and individual human emotions as a person’s response to such urban contexts. However, the integration of such human urban emotions into citizen-centric spatial planning processes is a major challenge in order to contribute to a fundamentally changing understanding of spatial and regional planning.

B
Background

The goal of the Urban Emotions project is to analyse the trends of real-time human sensory and crowdsourcing approaches in social networks for the extraction of contextual emotion information for decision support in spatial planning and to develop it further to an innovative methodology for the domain of urban and regional planning. This methodology includes the correlation between emotions extracted from psycho-physiological smartband sensor measurements (People as Sensors) and different VGI datasets (Twitter, Instagram, Flickr, etc.). Herein, the topics of data privacy and handing personalised data are inherently considered.

R
Results

The results of the Urban Emotions project will give new and additional insights into the complex human-sensor-city relationship. These insights will be enabled by means of novel visualization techniques of the data analysed and their preparation for urban planning processes to validate existing planning measures. This is demonstrated through a showcase in the cities of Heidelberg, Kaiserslautern and Boston (USA). Planning practitioners receive an appropriate overview of methods which can be used as an additional recommendation for further action.

 


Key Publications
Resch, B., Summa, A., Zeile, P. and Strube, M. (2016) Citizen-centric Urban Planning through Extracting Emotion Information from Twitter in an Interdisciplinary Space-Time-Linguistics Algorithm. Urban Planning, 1(2), pp. 114-127, DOI: 10.17645/up.v1i2.617.
Resch, B., Summa, A., Sagl, G., Zeile, P. and Exner, J.-P. (2015) Urban Emotions – Geo-semantic Emotion Extraction from Technical Sensors, Human Sensors and Crowdsourced Data. In: Gartner, G. and Haosheng Huang (eds.) (2015) Progress in Location-Based Services 2014, Springer International Publishing, Switzerland, pp. 199-212.
Resch, B., Sudmanns, M., Sagl, G., Summa, A., Zeile, P. and Exner, J.-P. (2015) Crowdsourcing Physiological Conditions and Subjective Emotions by Coupling Technical and Human Mobile Sensors. GI_Forum – Journal for Geographic Information Science, 1-2015, pp. 514-524.
Zeile, P., Resch, B., Loidl, M. and Petutschnig, A. (2016) Urban Emotions Cycling Experience – Enriching Traffic Planning for Cyclists with Human Sensor Data. GI_Forum – Journal for Geographic Information Science, 1-2016, pp. 204-216, DOI:10.1553/giscience2016_01_s204.
Team
Bernd Resch (project lead)
Günther Sagl, Ourania Kounadi, Mark Padgham, Andreas Petutschnig, Stefan Zimmer, Martin Sudmanns, Anja Summa, Veronika Priesner, Clemens Havas
Project partners
2017-11-13T15:33:38+00:00