A glimpse on big data analytics in the framework of marketing strategies

Mining and analyzing the valuable knowledge hidden behind the amount of data available in social media is becoming a fundamental prerequisite for any effective and successful strategic marketing campaign. Anyway, to the best of our knowledge, a systematic analysis and review of the very recent liter...

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Bibliographic Details
Published in:Soft computing (Berlin, Germany) Vol. 22; no. 1; pp. 325 - 342
Main Authors: Ducange, Pietro, Pecori, Riccardo, Mezzina, Paolo
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2018
Springer Nature B.V
Subjects:
Artificial Intelligence
Big Data
Competitive advantage
Computational Intelligence
Control
Data analysis
Engineering
Internet
Machine learning
Market strategy
Marketing
Mathematical Logic and Foundations
Mechatronics
Methodologies and Application
Real time
Robotics
Social networks
Society
Social networks
Social big data
Strategic marketing
Social media
ISSN:1432-7643, 1433-7479
Online Access:Get full text
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Summary:Mining and analyzing the valuable knowledge hidden behind the amount of data available in social media is becoming a fundamental prerequisite for any effective and successful strategic marketing campaign. Anyway, to the best of our knowledge, a systematic analysis and review of the very recent literature according to a marketing framework is still missing. In this work, we intend to provide, first and foremost, a clear understanding of the main concepts and issues regarding social big data, as well as their features and technologies. Secondly, we focus on marketing, describing an operative methodology to get useful insights from social big data. Then, we carry out a brief but accurate classification of recent use cases from the literature, according to the decision support and the competitive advantages obtained by enterprises whenever they exploit the analytics available from social big data sources. Finally, we outline some open issues and suggestions in order to encourage further research in the field.
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ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-017-2536-4