Abstract
In the context of smart cities and Internet of Things (IoT), there are many trending contents on the social networks that reflect the picture of the community or their interest. In this paper, we propose a model that automatically collect trending social data and analyze them automatically. The model explores trending contents, overall attitude of textual contents and the relationships among the participated users. The analysis of the data collected involves the analysis of the user as well as the community in terms of interest, embedded tags, and the corresponding contents. The model is trained using data collected from Twitter, the famous growing social network, using hashtags, emoticons, geo-tags, and user profiles. We focus in this work on the Arabic contents to visualize the resulted emotions on a real world map.