Natalya Dmitrieva, G. Chistyakova, I. Sandrakova, Tamara V. Frolova, N. Omarova
{"title":"Digital Space Analytics in Studying the Popularity of Microtourism Objects","authors":"Natalya Dmitrieva, G. Chistyakova, I. Sandrakova, Tamara V. Frolova, N. Omarova","doi":"10.2991/aebmr.k.220208.011","DOIUrl":null,"url":null,"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.","PeriodicalId":237433,"journal":{"name":"Proceedings of the International Scientific and Practical Conference Strategy of Development of Regional Ecosystems “Education-Science-Industry” (ISPCR 2021)","volume":"112 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Scientific and Practical Conference Strategy of Development of Regional Ecosystems “Education-Science-Industry” (ISPCR 2021)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/aebmr.k.220208.011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.