A new method for evaluating tour online review based on grey 2‐tuple linguistic

A new method for evaluating tour online review based on grey 2‐tuple linguistic Purpose – Tour social network data that are heterogeneous contain not only the quantitative structured evaluation data, but also the qualitative non‐structured data. This is a big data scenario. How to evaluate tour online review and then recommend to potential tourists quickly and accurately are important parts of social responsibility of tour companies. The purpose of this paper is to propose a new method for evaluating tour online review based on grey 2‐tuple linguistic. Design/methodology/approach – The phenomenon of “poor information” exists in some big data scenario. According to social responsibility, grey 2‐tuple linguistic evaluation model for tour online review is proposed. Findings – Tour social networks contain data that are valuable to each individual on tourism industry's value chain. Grey 2‐tuple linguistic evaluation model can be used for evaluating tour online reviews. This is a systems thinking method that takes social responsibility into account. Research limitations/implications – Due to the complex links among reviewers in social network, network mining approaches and models are expected to be added to this research in the near future. Practical implications – Grey 2‐tuple linguistic evaluation method can contribute to the future research on evaluating a variety of tour social network comment data in the real world. Originality/value – A new evaluation method for making evaluation and recommendations based on tour social network comment information is proposed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Kybernetes Emerald Publishing

A new method for evaluating tour online review based on grey 2‐tuple linguistic

Kybernetes, Volume 43 (3/4): 13 – Apr 1, 2014

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Publisher
Emerald Publishing
Copyright
Copyright © 2014 Emerald Group Publishing Limited. All rights reserved.
ISSN
0368-492X
DOI
10.1108/K-06-2013-0123
Publisher site
See Article on Publisher Site

Abstract

Purpose – Tour social network data that are heterogeneous contain not only the quantitative structured evaluation data, but also the qualitative non‐structured data. This is a big data scenario. How to evaluate tour online review and then recommend to potential tourists quickly and accurately are important parts of social responsibility of tour companies. The purpose of this paper is to propose a new method for evaluating tour online review based on grey 2‐tuple linguistic. Design/methodology/approach – The phenomenon of “poor information” exists in some big data scenario. According to social responsibility, grey 2‐tuple linguistic evaluation model for tour online review is proposed. Findings – Tour social networks contain data that are valuable to each individual on tourism industry's value chain. Grey 2‐tuple linguistic evaluation model can be used for evaluating tour online reviews. This is a systems thinking method that takes social responsibility into account. Research limitations/implications – Due to the complex links among reviewers in social network, network mining approaches and models are expected to be added to this research in the near future. Practical implications – Grey 2‐tuple linguistic evaluation method can contribute to the future research on evaluating a variety of tour social network comment data in the real world. Originality/value – A new evaluation method for making evaluation and recommendations based on tour social network comment information is proposed.

Journal

KybernetesEmerald Publishing

Published: Apr 1, 2014

Keywords: Social network; Corporate social responsibility; 2‐tuple linguistic; Grey systems; Tour online review evaluation

References

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