Towards the Paradigm of Information Warehousing: Application to Twitter

Abstract

Over the last decade, social media have dominated our lives. The exploding number of data produced by these platforms triggered a wave of research works that mainly focus on the storage and analysis of this data. In this paper, we propose an original information warehouse architecture for the storage and analysis of social media information. A multidimensional model is defined and the information is extracted, transformed and loaded in the warehouse using ETL (Extract, Transform, Load). The described framework is implemented for Twitter and a data mining analysis is performed on the collected tweets using a clustering algorithm to uncover most discussed topics. The preliminary results are satisfactory and the proposed paradigm can be applied for various information sources such as newspapers and scientific papers.