State of the Art in Knowledge Extraction from Online Polls: A Survey of Current Technologies

The ongoing research and development in the field of Natural Language Processing has lead to a great number of technologies in its context. There have been major benefits when it comes to bringing together the worlds of natural language and semantic technologies, so more and more potential areas of application emerge. One of these is the subject of this paper, in particular the possible ways of knowledge extraction from single-question online polls. With concepts of the Social Web, internet users want to contribute and express their opinion. As a consequence, the popularity of online polls is rapidly increasing; they can be found in news articles of media sites, on blogs etc. It would be desirable to bring intelligence to the application of polls by using technologies of the SemanticWeb and Natural Language Processing as this would allow to build a great knowledge base and to draw conclusions from it. This paper surveys the current landscape of tools and state-of-the-art technologies and analyses them with regard to pre-defined requirements that need to be accomplished, in order to be useful for extracting knowledge from the results generated by online polls.