| Title |
Crowd-sensing Images to Understand Citizens' Emotions, Issues and Interests |
| ID_Doc |
44526 |
| Authors |
De Michele, R; Furini, M; Montangero, M |
| Title |
Crowd-sensing Images to Understand Citizens' Emotions, Issues and Interests |
| Year |
2019 |
| Published |
|
| Abstract |
Many studies are beginning to gather data with a crowd-sensing approach in order to understand citizens' opinions and thoughts, because these data are more and more crucial for the smart management of a city. So far, the focus is mainly on textual data, but recent approaches revealed the wealth of information that can be found in multimedia contents. In this paper, we propose a crowd-sensing approach that exploits the popularity and the pervasiveness of the Instagram application to understand citizens emotions, issues and interests. The idea is to map the colors of the images into a psychological emotional model and to measure the significance of the words used in the caption of the images. Results showed that the use of the visual contents might be misleading, due to the large use of image filters that alter the real contents of the images, but also disclosed that captions might give insights about citizens that can be very useful to smartly manage a city. |
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