Study on the Rural Tourism Image of She Ethnic Group Based on Network Text Mining Analysis

DOI

10.2991/icemi-16.2016.40How to use a DOI?

Keywords

Network Text;ROST; She Ethnic Group; Rural Tourism

Abstract

Network text mining analysis is an important method for the evaluation of tourism destination image, through the collection, screening and analysis of network data, the tourists' perceptual information can be obtained, the attributes and characteristics of tourism destination image can be studied and judged.In this paper, ROST text analysis software has been used, Guangdong HuangLongyan She Ethnic Group Style Tourist Area has been taken as an Example, the tourists' after-sales feedback evaluation and travel notes from Tongcheng, com, Ctrip.com and other travel websites have been collected, high frequency characteristic words of tourism image have been dug and extracted, positive and negative effective factors of tourists' evaluation have been analyzed, it is found that She nationality brigade style, karst cave wonders and others are the most recognized image perception by tourists; but the problem of negative evaluation on the charge of entrance tickets and parking, temples and others is also very prominent.Therefore, the tourist area needs to change the operation mode of the single ticket economy, by increasing supply projects of diversity of scenic spots, transforming rural experience tourism facilities and inheriting and cultivating the unique culture of the minority nationality, so that the innovation and development of tourism industry in Guangdong Zhang Xi She Nationality Area and regional rural can be promote.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xinlei Wu
AU  - Ying Zhang
PY  - 2016/07
DA  - 2016/07
TI  - Study on the Rural Tourism Image of She Ethnic Group Based on Network Text Mining Analysis
BT  - Proceedings of the 2016 International Conference on Economics and Management Innovations
PB  - Atlantis Press
SP  - 200
EP  - 204
SN  - 2352-538X
UR  - https://doi.org/10.2991/icemi-16.2016.40
DO  - 10.2991/icemi-16.2016.40
ID  - Wu2016/07
ER  -