{"title":"利用文本自愿地理信息模拟基于自然的活动:以新西兰奥特罗阿为例","authors":"E. Egorova","doi":"10.5311/josis.2021.23.157","DOIUrl":null,"url":null,"abstract":"A boom in volunteered geographic information has led to extensive data-driven exploration and modeling of places. While many studies have used such data to explore human-environment interaction in urban settings, few have investigated natural, non-urban settings. To address this gap, this study systematically explores the content of online reviews of nature-based recreation activities, and develops a fine-grained hierarchical model that includes 28 aspects grouped into three main domains: activity, settings, and emotions/cognition. It further demonstrates how the model can be used to explore the variation in recreation experiences across activities, setting the stage for the analysis of the spatio-temporal variations in recreation experiences in the future. Importantly, the study provides an annotated corpus that can be used as a training dataset for developing methods to automatically capture aspects of recreation experiences in texts.","PeriodicalId":45389,"journal":{"name":"Journal of Spatial Information Science","volume":" ","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2021-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Using textual volunteered geographic information to model nature-based activities: A case study from Aotearoa New Zealand\",\"authors\":\"E. Egorova\",\"doi\":\"10.5311/josis.2021.23.157\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A boom in volunteered geographic information has led to extensive data-driven exploration and modeling of places. While many studies have used such data to explore human-environment interaction in urban settings, few have investigated natural, non-urban settings. To address this gap, this study systematically explores the content of online reviews of nature-based recreation activities, and develops a fine-grained hierarchical model that includes 28 aspects grouped into three main domains: activity, settings, and emotions/cognition. It further demonstrates how the model can be used to explore the variation in recreation experiences across activities, setting the stage for the analysis of the spatio-temporal variations in recreation experiences in the future. Importantly, the study provides an annotated corpus that can be used as a training dataset for developing methods to automatically capture aspects of recreation experiences in texts.\",\"PeriodicalId\":45389,\"journal\":{\"name\":\"Journal of Spatial Information Science\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2021-12-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Spatial Information Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5311/josis.2021.23.157\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GEOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Spatial Information Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5311/josis.2021.23.157","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOGRAPHY","Score":null,"Total":0}
Using textual volunteered geographic information to model nature-based activities: A case study from Aotearoa New Zealand
A boom in volunteered geographic information has led to extensive data-driven exploration and modeling of places. While many studies have used such data to explore human-environment interaction in urban settings, few have investigated natural, non-urban settings. To address this gap, this study systematically explores the content of online reviews of nature-based recreation activities, and develops a fine-grained hierarchical model that includes 28 aspects grouped into three main domains: activity, settings, and emotions/cognition. It further demonstrates how the model can be used to explore the variation in recreation experiences across activities, setting the stage for the analysis of the spatio-temporal variations in recreation experiences in the future. Importantly, the study provides an annotated corpus that can be used as a training dataset for developing methods to automatically capture aspects of recreation experiences in texts.