Use of Twitter stream data for trend detection of various social media sites in real time

Abstract

Emergence of social networks such as Twitter has enhanced communication among large proportions of participants sharing enormous volumes of data. Categorization and analysis of the data in-depth will enable to generate valuable insights and information. In this paper, a new method is presented to find the trending content and trending topics of various social media networks using real time data shared on Twitter. The insights on current trending content generated by the proposed system will be of high importance as majority of the external social media networks doesn't directly publish any real time data related to trends or most interesting content within itself. © 2014 Springer International Publishing Switzerland.