Diversity-Aware Clustering of SIOC Posts

Sentiment analysis as well as topic extraction and named entity recognition are emerging methods used in the field of Web Mining. Next to SQL-like querying and according visualization, new ways of organization have become possible. In this demo paper we apply efficient clustering algorithms that stem from the image retrieval field to sioc:Post entities, blending similarity scores of sentiment and covered topics. We demonstrate the system with a visualization component that combines different diversity aspects within microposts by Twitter users and a static news article collection.