Ghasem Javadi; Mohammad Taleai
Abstract
Public satisfaction is a multidimensional and dynamic concept that changes over time, so it must be evaluated at appropriate times. A major challenge for this evaluation, especially in large geographical areas such as one country, is the lack of regular procedures and updated relevant index values. In ...
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Public satisfaction is a multidimensional and dynamic concept that changes over time, so it must be evaluated at appropriate times. A major challenge for this evaluation, especially in large geographical areas such as one country, is the lack of regular procedures and updated relevant index values. In recent years, several indicators have been presented based on traditional methods of data collection, including the use of questionnaires, to measure public satisfaction. Since, in recent years, the use of User Generated Geo-Content (UGGC) has been widely considered, in this research, with a new perspective by using of location-based social networks (LBSNs), extraction of information and criteria that can somehow reflect public satisfaction has been done. Finally, considering the uncertainties in the input data and the definition of public satisfaction, a fuzzy inference system was used to evaluate and compare public satisfaction in Iranian provinces. The extracted indices in this study, include negative/positive tweet ratio, the ratio of joy and love tweets to all tweets, and the ratio of sadness, anger and fear tweets to all tweets. The results of the proposed method resulted in the classification of the provinces of Iran from favorable to unfavorable situations. The results of this study demonstrated the potential of UGGC for public satisfaction assessment in the role of complementary data rather than as an alternative to official data. The proposed method in this study is a step towards evaluating public satisfaction using data shared by users on location-based social networks.
