Using textual volunteered geographic information to model nature-based activities: A case study from Aotearoa New Zealand

IF 1.8 Q2 GEOGRAPHY
E. Egorova
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引用次数: 4

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.
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
志愿提供地理信息的热潮导致了广泛的数据驱动的地方探索和建模。虽然许多研究使用这些数据来探索城市环境中人与环境的相互作用,但很少有研究调查自然、非城市环境。为了解决这一差距,本研究系统地探讨了基于自然的娱乐活动的在线评论内容,并开发了一个细粒度的分层模型,该模型包括28个方面,分为三个主要领域:活动、设置和情感/认知。该研究进一步证明了该模型可以用于探索不同活动中游憩体验的变化,为未来分析游憩体验的时空变化奠定了基础。重要的是,该研究提供了一个带注释的语料库,可以用作开发自动捕获文本中娱乐体验方面的方法的训练数据集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.10
自引率
0.00%
发文量
5
审稿时长
9 weeks
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