Big Data Analytics on the Characteristic Equilibrium of Collective Opinions in Social Networks

Big data are products of human collective intelligence that are exponentially increasing in all facets of quantity, complexity, semantics, distribution, and processing costs in computer science, cognitive informatics, web-based computing, cloud computing, and computational intelligence. This paper p...

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Bibliographic Details
Published in:International journal of cognitive informatics & natural intelligence Vol. 8; no. 3; pp. 29 - 44
Main Authors: Wang, Yingxu, Wiebe, Victor J
Format: Journal Article
Language:English
Published: Hershey IGI Global 01.07.2014
Subjects:
Analytics
Big Data
Cloud computing
Cognitive ability
Computer applications
Data analysis
Data management
Data mining
Data processing
Fuzzy
Fuzzy set theory
Informatics
Information processing
Intelligence
Machine learning
Mathematical models
Methods
Semantics
Social interactions
Social networks
Social organization
Sociology
ISSN:1557-3958, 1557-3966
Online Access:Get full text
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Summary:Big data are products of human collective intelligence that are exponentially increasing in all facets of quantity, complexity, semantics, distribution, and processing costs in computer science, cognitive informatics, web-based computing, cloud computing, and computational intelligence. This paper presents fundamental big data analysis and mining technologies in the domain of social networks as a typical paradigm of big data engineering. A key principle of computational sociology known as the characteristic opinion equilibrium is revealed in social networks and electoral systems. A set of numerical and fuzzy models for collective opinion analyses is formally presented. Fuzzy data mining methodologies are rigorously described for collective opinion elicitation and benchmarking in order to enhance the conventional counting and statistical methodologies for big data analytics.
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ISSN:1557-3958
1557-3966
DOI:10.4018/IJCINI.2014070103