Data warehouse design approaches from social media: review and comparison

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• 作者：Imen Moalla ; Ahlem Nabli ; Lotfi Bouzguenda…
• 关键词：Business intelligence ; Data warehouse ; OLAP ; Social media
• 刊名：Social Network Analysis and Mining
• 出版年：2017
• 出版时间：December 2017
• 年：2017
• 卷：7
• 期：1
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Data Mining and Knowledge Discovery; Applications of Graph Theory and Complex Networks; Game Theory, Economics, Social and Behav. Sciences; Statistics for Social Science, Behavorial Science, Education
• 出版者：Springer Vienna
• ISSN：1869-5469
• 卷排序：7

文摘

With the rise of social media in our life, several decision makers have worked on these networks to make better decisions. In order to benefit from the data issued from these media, many researchers focused on helping companies understand how to perform a social media competitive analysis and transform these data into knowledge for decision makers. A high number of users interact at any time on different ways in social media such as by expressing their opinions about products, services or transaction related to the organization which can prove very helpful for making better projections. In this paper, we provide a literature review on data warehouse design approaches from social media. More precisely, we start by introducing the main concepts of data warehouse and social media. We also propose two classes of data warehouse design approaches from social media (behavior analysis and integration of sentiment analysis in data warehouse schema) and expose for each one the most representative existing works. Afterward, we propose a comparative study of the existing works.