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.
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.
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.
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.
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.
A new evaluation method for making evaluation and recommendations based on tour social network comment information is proposed.
The relevant researches done in this paper are supported by the NUAA Fundamental Research Funds (No. NS2013080).
Mi, C., Shan, X., Qiang, Y., Stephanie, Y. and Chen, Y. (2014), "A new method for evaluating tour online review based on grey 2-tuple linguistic", Kybernetes, Vol. 43 No. 3/4, pp. 601-613. https://doi.org/10.1108/K-06-2013-0123Download as .RIS
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