Majority OWA operator for opinion rating in social media

In recent years, the acquisition of products and services via Internet has grown exponentially. Today, a person goes through different websites in search of better alternatives and prices. In this searching process, he/she uses social media applications to examine the opinions of others who have pur...

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Veröffentlicht in:Soft computing (Berlin, Germany) Germany), 2016-03, Vol.20 (3), p.1047-1055
Hauptverfasser: Peláez, J. I., Bernal, R., Karanik, M.
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creator Peláez, J. I.
Bernal, R.
Karanik, M.
description In recent years, the acquisition of products and services via Internet has grown exponentially. Today, a person goes through different websites in search of better alternatives and prices. In this searching process, he/she uses social media applications to examine the opinions of others who have purchased such services or products. Also, the seller offers summarized information of buyers’ valuation by a satisfaction value on a predefined scale (expressed with a system of stars or linguistic labels). This number is calculated using an arithmetic mean and, in many cases, does not adequately reflect all users’ opinions. In this article, a new consensus operator called selective aggregated majority ordered weighted averaging (SAM-OWA) is proposed. It is based on the opinions of the majority though also considering the opinion of the minority. SAM-OWA calculates the individual weights of each value of the satisfaction scale, using the number of votes obtained (cardinality). The mathematical foundation of SAM-OWA operator and some application examples to improve the results obtained by the arithmetic mean are presented.
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subjects Aggregates
Arithmetic
Artificial Intelligence
Computational Intelligence
Control
Customer services
Decision making
Digital media
Engineering
Linguistics
Mathematical analysis
Mathematical Logic and Foundations
Mechatronics
Methodologies and Application
Robotics
Social networks
User generated content
title Majority OWA operator for opinion rating in social media
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