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Emotional maps based on social networks data to analyze cities emotional structure and measure their emotional similarity

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Abstract The present study utilizes the social media data to sample from people's emotion in different places based on their facial expressions, for analyzing emotions distribution in a city and… Click to show full abstract

Abstract The present study utilizes the social media data to sample from people's emotion in different places based on their facial expressions, for analyzing emotions distribution in a city and comparing the emotional similarity between cities. Experiencing various emotions gives birth to different facial expressions which usually have similar patterns for individuals. Extracting these patterns from face images and analyzing them makes it possible to extract related emotion associated with the shared photos. Since geo-tagged images include metadata about the geographical location, estimation of emotions spatial distribution is possible. The distribution of four emotions: anger, disgust, happiness, and surprise in twelve cities, included Athens, Beijing, Berlin, Brussels, Buenos Aires, Copenhagen, Helsinki, Melbourn, New York, Ottawa, Paris, and Prague is investigated by analyzing geo-tagged photos shared on Flickr. After facial expressions extraction, the spatial distribution functions of the emotions are calculated by kernel density estimation method. Emotional maps for cities are created using extracted features of Fourier transform spectrum of the spatial distributions which are robust against rotation and translation. Afterward, similar cities based on their emotional structure are clustered into appropriate groups. The results are beneficial for urban planners and social researchers to analyze the effect of the environment on peoples' emotions. Furthermore, this could guide them to make right policies to improve the quality of life. Considering the four studied emtions, New York has the highest ratio in anger, Ottawa has the highest proportion of happiness and Copenhagen has the highest ratio in both surprise and disgust among the studied cities. In addition, an attempt is made to calculate the percentage of different emotions and dispersion of them as important emotional factors in understanding the emotional structure of cities. To measure the dispersion of happiness the coefficient of variation is computed. The results show that happiness dispersion in Berlin has a more uniform distribution according to the collected data. It seems both coefficients of variation and emotions percentage may be jointly effective in urban planning and cities comparison based on people emotional mode.

Keywords: emotional similarity; emotional maps; cities emotional; emotional structure; distribution

Journal Title: Cities
Year Published: 2019

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