Weaving Twitter stream into Linked Data a proof of concept framework

Abstract

Twitter is one of the most popular and well known micro blogging platforms. Its usage in all walks of life as a short message service makes it a highly valuable and trendy asset of today's web. But the knowledge and content delivered by Twitter explicitly or implicitly as short messages remains mostly unstructured and hidden for machine usage. In this paper, we have addressed the aforementioned problems by using the Semantic Web and Linked Data technologies. We explore an integrated approach by building a proof of concept framework, which uses Semantic Web technologies to triplify and link the unstructured content of tweets with Linked Data clouds as structured data. We are of the view that this proof of concept framework will be helpful in investigation of case studies like opinion mining, trend analysis in various settings and more importantly will bring the Social Web closer to the Semantic Web. In future we will extend our proposed framework in the domain of terrorism informatics.