Twitter analytics

Abstract

With the inception of the Twitter microblogging platform in 2006, a myriad of research efforts have emerged studying different aspects of the Twittersphere. Each study exploits its own tools and mechanisms to capture, store, query and analyze Twitter data. Inevitably, platforms have been developed to replace this ad-hoc exploration with a more structured and methodological form of analysis. Another body of literature focuses on developing languages for querying Tweets. This paper addresses issues around the big data nature of Twitter and emphasizes the need for new data management and query language frameworks that address limitations of existing systems. We review existing approaches that were developed to facilitate twitter analytics followed by a discussion on research issues and technical challenges in developing integrated solutions.