信息资源管理学报 ›› 2018, Vol. 8 ›› Issue (3): 93-101.doi: 10.13365/j.jirm.2018.03.093

• 研究论文 • 上一篇    下一篇

旅游舆情网络关注度城市差异——来自289个城市百度指数的实证研究

刘嘉毅 陈玲 陶婷芳   

  • 收稿日期:2018-01-15 出版日期:2018-07-26 发布日期:2018-07-26
  • 作者简介:刘嘉毅,男,博士,副教授,研究方向为旅游舆情与文化旅游研究,Email:ljiayiw@163.com;陈玲,女,博士,讲师,研究方向为舆情管理与产业经济研究;陶婷芳,女,教授,博士生导师,研究方向为旅游产业运营与旅游演艺研究。
  • 基金资助:

    本文系教育部人文社会科学青年基金项目(16YJC630069)的阶段性研究成果。

Urban Differences in Network Attention to Tourism Public Opinion:An Empirical Study from Baidu Index of 289 Cities

Liu Jiayi Chen Ling Tao Tingfang   

  • Received:2018-01-15 Online:2018-07-26 Published:2018-07-26

摘要:

基于289个城市对“天价虾”舆情的百度指数,实证分析旅游舆情网络关注度城市差异及其影响因素。研究发现:①旅游舆情网络关注度总体呈现高峰正偏的非正态分布特征,城市绝对差异大;东部、中部、西部城市对旅游舆情的网络关注度逐渐递减,网络关注度相对差异从大到小依次为西部、东部、中部城市,城市规模越大,其旅游舆情网络关注度越高。②旅游舆情高关注城市、较高关注城市、中等关注城市、低关注城市呈现空间交叉共生分布格局,中等关注为主体;高关注城市多在东部,低关注城市多在西部;省会城市与直辖市是高关注城市的绝对主体,北上广位居位序前三。③人均收入水平、人口规模、信息化程度、城市级别、旅游市场规模等表征城市异质性的变量显著影响旅游舆情网络关注度;空间距离对旅游舆情网络关注度的影响存在区域异质性;旅游目的地同质性正向影响城市对旅游舆情的网络关注。

关键词: 旅游舆情, 网络关注度, 城市差异, 百度指数

Abstract:

Based on the Baidu index of "astronomically expensive shrimp" public opinion from 289 cities, this paper analyzes the urban differences and their influencing factors of network attention to tourism public opinion. The results show that: (1) The network attention of tourism public opinion is generally non-normal distributions with high kurtosis and positive skewness, the absolute difference of network attention to tourism public opinion is large, and it gradually decreases from the eastern, central to western cities, while relative differences from large to small is followed by the western, eastern, central cities.It shows that the larger the city scale, the higher the network attention degree on tourism public opinion. (2) 289 Cities are classified into four categories by network attention degree of tourism public opinion, such as the highest attentive cites, the higher attentive cites, the medium attentive cites and low attentive cites. It shows a spatial cross-symbiotic distribution pattern, and the medium attentive cites have a largest ratio. The highest attentive cites are mainly in the east, and the low attentive cites are mainly in the west; The capital cities and municipalities are the absolute main part of the highest attentive cites. Beijing, Shanghai, Guangzhou are the first three places in the rank. (3) The variables of urban heterogeneity, such as the level of per person income, the population size, the degree of informatization, the city level and the scale of tourism industry, have a significant impact on network attention to tourism public opinion. The influence of spatial distance on network attention of tourism public opinion is differenced by regional heterogeneity. Tourism destination homogeneity has a positive impact on network attention to tourism public opinion.

Key words: Tourism public opinion, Network attention, Urban differences, Baidu index

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