Assessment and visualization of geographically distributed event-related sentiments by mining social networks and news
In this paper we present a method/tool for integrating heterogeneous data, assessing and visualizing sentiments related to big impact events in geographically confined populations. The data employed are official statistical information provided by governments, news web sites and user submitted georeferenced comments retrieved from various social networks. Sentiment analysis is applied to the retrieved comments and results are visualized on interactive maps, thus providing an effective tool for decision makers and analysts to evaluate how socioeconomic factors can influence the mood and the opinion of a specific area. The method is designed to assist city planners, business managers or social scientists for strategic planning and decision making. Furthermore, the experimental evaluation showed that the proposed method is robust, achieves state-of-the-art performance and allows an easy-exploration of big, distributed and heterogeneous information.