Digital Space Analytics in Studying the Popularity of Microtourism Objects

Natalya Dmitrieva, G. Chistyakova, I. Sandrakova, Tamara V. Frolova, N. Omarova
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Abstract

Since March 2020, against the backdrop of a massive decline in the global tourism market, there has been an increase in interest in micro-tourism in all countries – travelling within the region of residence or neighboring regions. The study is aimed at solving a serious problem of the development of micro-tourism, which consists in the lack of sufficient data on specific tourist sites of certain territories, as well as tools for their analysis, which make it possible to predict tourist flows, as well as to develop and promote both individual sites and the territory as a whole. Most of the existing approaches to analytics of the digital space in micro-tourism involve the use of data that tracks actions already taken by tourists, in most cases relying on their digital footprint associated with financial transactions. At the micro-tourism level, there are many tourist sites, the popularity of which cannot be analyzed in this way, for example, natural attractions. Using such digital space analytics tools as search queries and hashtags in social networks, the authors propose to assess the potential interest in tourist sites and their real popularity, to rank objects by these indicators and thus to predict tourist flows, distribute investments and highlight groups of objects for priority development. and promotion. The proposed approach has been tested on the example of a municipal district with thirteen tourist sites. It is inexpensive, understandable and convenient for specialists of any level of training. The ranking of tourist sites can be carried out both by tour operators and by municipal or regional authorities.
微旅游对象流行度研究中的数字空间分析
自2020年3月以来,在全球旅游市场大幅下滑的背景下,所有国家对微型旅游的兴趣都有所增加,即在居住地区或邻近地区旅行。这项研究的目的是解决发展微型旅游的一个严重问题,这个问题是缺乏关于某些领土的具体旅游地点的充分数据以及分析这些地点的工具,从而能够预测游客流量,以及发展和促进个别景点和整个领土。大多数现有的微型旅游数字空间分析方法涉及使用跟踪游客已经采取的行动的数据,在大多数情况下依赖于他们与金融交易相关的数字足迹。在微观旅游层面,有许多旅游景点,其受欢迎程度无法用这种方法分析,例如自然景点。利用诸如社交网络中的搜索查询和标签等数字空间分析工具,作者建议评估对旅游景点的潜在兴趣及其实际受欢迎程度,根据这些指标对景点进行排名,从而预测游客流量,分配投资并突出优先开发的景点群。和推广。所提出的方法已在一个拥有13个旅游景点的市辖区进行了测试。对于任何水平的培训专家来说,它都是便宜、易懂和方便的。旅游景点的排名既可以由旅游经营者进行,也可以由市政或地区当局进行。
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