Abstract

KRAIEM, Maha Ben  and  FEKI, Jamel. Building a Data Warehouse for Social Media: Review and Comparison. Comp. y Sist. [online]. 2024, vol.28, n.1, pp.19-39.  Epub June 10, 2024. ISSN 2007-9737.  https://doi.org/10.13053/cys-28-1-4677.

The significant advancements in technology over the past few decades have given rise to a relatively straightforward array of Internet applications based on open source software. These applications and services aim to enhance online collaboration for a broad audience, particularly through social networking sites. These platforms have transformed the dynamics of online interaction and information exchange, with millions of users regularly engaging and sharing various digital content. Users express their thoughts and opinions on diverse topics, contributing valuable insights for personal, academic, and commercial purposes. However, the sheer volume and rapid generation of this data present a challenge for decision-makers and the underlying technologies to extract meaningful insights. To leverage the data derived from social networks, researchers have focused on assisting companies in comprehending how to conduct competitive analyses and convert this data into actionable knowledge. This paper offers a comprehensive literature review on data warehouse approaches derived from social networks. We commence by introducing fundamental concepts of data warehousing and social networks, followed by the presentation of three categories of data warehouse approaches, along with an overview of the most notable existing works within each category. Subsequently, we conduct a comparative analysis of these existing works.

Keywords : Data warehouse; social media; opinion analysis; business intelligence; OLAP.

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