{"title":"Exploring Public Interest in Limited-Use Areas and Compensation from Airports in Poland: A Google Trends Analysis","authors":"M. Bełej","doi":"10.2478/remav-2024-0025","DOIUrl":null,"url":null,"abstract":"\n This article evaluates online social behavior regarding the establishment of limited-use areas (LUAs) around the airports in Warsaw and Gdansk. The study relied mainly on an analysis of Google Trends statistics, in particular the dynamics of keyword searches. The article suggests that assessments of online behavior can provide a deeper understanding of social behavior. The study involved an OLS regression analysis and a causal impact analysis of the intervention based on a Bayesian structural time-series model. This article analyses different phases of an information society's activity, from the introduction of LUAs around airports to the deadline for submitting compensation claims. The results indicate that the number of searches for the keyword \"compensation\" increased significantly after the introduction of LUAs and that RSV decreased after the end of the compensation process, which confirms that the intervention significantly influenced the analyzed time series.","PeriodicalId":510834,"journal":{"name":"Real Estate Management and Valuation","volume":" 41","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Real Estate Management and Valuation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/remav-2024-0025","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
This article evaluates online social behavior regarding the establishment of limited-use areas (LUAs) around the airports in Warsaw and Gdansk. The study relied mainly on an analysis of Google Trends statistics, in particular the dynamics of keyword searches. The article suggests that assessments of online behavior can provide a deeper understanding of social behavior. The study involved an OLS regression analysis and a causal impact analysis of the intervention based on a Bayesian structural time-series model. This article analyses different phases of an information society's activity, from the introduction of LUAs around airports to the deadline for submitting compensation claims. The results indicate that the number of searches for the keyword "compensation" increased significantly after the introduction of LUAs and that RSV decreased after the end of the compensation process, which confirms that the intervention significantly influenced the analyzed time series.