Converting Opinion into Knowledge: Improving User Experience and Analytics of Online Polls

A vast majority of internet users has adopted new ways and possibilities of interaction and information exchange on the social web. Individuals are becoming accustomed to contribute and express their opinion on various platforms and websites. Commercial online polls allow operators of online newspapers, blogs and other forms of media sites to provide such services to their users. Consequently, their popularity is rapidly increasing and more and more potential areas of application emerge. However, in most cases the expressed opinions are stored and displayed without any further actions and the knowledge that lies in the answers is discarded. This research paper explores the possibilities, advantages and limits of applying semantic technologies to these online polls. For this purpose, a list of requirements was assembled and possible system architectures for semantic knowledgebases were investigated with the focus on providing consistent and extensive data for further processing. In a next step, the current state of the art of relevant visualization technologies was analyzed and further research challenges were identified. Our results discuss possible applications within the scope of a challenging case study. A comprehensive data pool provided by our industry partner allows for testing various improvements to user experience and traction of the polling system.