基于网络文本与IPA模型分析的上海辰山植物园旅游形象感知研究

运用网络文本分析和IPA模型相结合的方法,研究大数据视野下的上海辰山植物园旅游形象感知。利用RostContent Mining软件分析,从携程、大众点评、美团等搜索旅游网站上筛选出上海辰山植物园旅游形象感知的高频词汇,绘制语义网络分析图。以高频词汇和语义网络分析结果为基础,运用IPA分析法构建分析模型,分析游客的目的地旅游体验要素结构和游客体验质量的评价。结果表明:游客体验要素的分值总体较高,表明游客的旅游体验评价关注点较为集中;重要性分值差异较大,表明游客对于旅游体验各要素的感知重要程度存在较大差异。根据研究结果,今后应从动植物多样性、自然生态环境、体验活动等5个方面进行改进提升,从而为游客提供高质量的游览体验。

Perception of Tourism Image of Chenshan Botanical Garden in Shanghai Based on Web Text Analysis and IPA model

The perception of tourism image of Chenshan Botanical Garden in Shanghai was studied based on web text analysis and IPA model.Through the use of Rost Content Mining software,the high-frequency vocabularies of Shanghai Chenshan Botanical Garden's tourism image perception were screened from Ctrip,Dazhong Dianping,Meituan,and other travel search websites,and then a semantic network analysis graph was illustrated.On the basis of high-frequency vocabulary and semantic network analysis graph,a collection of tourism experience factor structure and tourism experience quality evaluation data sets were compiled,and an IPA analysis method was used to construct a tourism image IPA analysis model based on web texts.The results show that the overall performance scores of various tourism experience factors are relatively high,which indicates that the tourist experience evaluation focuses more concentrated on visitors;the importance score difference is larger,indicating that the degree of importance of tourists' perception on various elements of tourism experience is quite different.According to the research results,the plant and animal diversity,natural ecological environment,and experience activities should be improved and upgraded in the future so as to provide tourists with a high quality tour experience.