游客目的地印象分析

Tourist Destination Impression Analysis

旅游目的地作为旅游活动开展的载体,近年来面临日趋增大的竞争压力。当前,中国各地区旅游品牌声誉度呈现发展不均衡的态势,怎样提升景区及酒店等旅游目的地美誉度,吸引优质游客、扩大品牌影响、提高竞争能力,成为各地区文旅主管部门和旅游相关企业关注的重点问题。游客满意度与目的地美誉度紧密相关,游客对旅游目的地的满意度越高,目的地美誉度就越大。本文通过分析景区及酒店等旅游目的地的游客互联网评价,在TF-IDF模型基础上,提出综合考虑词频与时间跨度的TF-ITH词汇热度计算模型,能够准确反映随时间变化的不同景区的游客评论热门词汇;引入预训练的Bert模型提取网评文本的观点,采用多元线性回归以MSE为评价指标来预测景区评分,为文本信息更加可观化提供一种新的方法;提出一种基于有效性的网络评论文本排序与筛选模型,能准确地剔除旅游目的地游客无效评论,从而为提升各地区旅游目的地的差异化竞争能力提供借鉴,进一步探索旅游目的地声誉塑造与维护的实现路径。

As a carrier of tourism activities, tourist destinations have faced increasing competitive pressure in recent years. At present, the reputation of tourism brands in various regions of China is developing unevenly. How to improve the reputation of tourist destinations such as scenic spots and hotels, attract high-quality tourists, expand brand influence and improve competitiveness has become a key issue of concern for cultural and tourism authorities and tourism-related enterprises in various regions. Tourist satisfaction is closely related to the reputation of the destination. The higher the tourist satisfaction with the destination, the greater the reputation of the destination. By analyzing the tourist internet evaluation of scenic spots, hotels and other tourist destinations, this paper proposes a TF-ITH vocabulary heat calculation model based on the TF-IDF model, which comprehensively considers the word frequency and time span, and can accurately reflect the hot words of tourist comments in different scenic spots over time;pre-trained Bert model is introduced to extract the viewpoint of online evaluation text, and multiple linear regression is used to predict the score of scenic spots with MSE as the evaluation index, which provides a new method for more observable text information. This paper proposes a text sorting and screening model of online comments based on effectiveness, which can accurately eliminate invalid comments from tourists in tourist destinations, so as to provide a reference for improving the differentiated competitiveness of tourist destinations in various regions, and further explore the realization path of reputation shaping and maintenance of tourist destinations.