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Supplementary Material for Komossa, Kong, Purves (2024) in Landscape Research

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DataCite Commons2024-05-28 更新2024-08-19 收录
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https://figshare.com/articles/dataset/Supplementary_Material_for_Komossa_Kong_Purves_2024_in_Landscape_Research/25908934
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This repository is created to archive the analytic process for a paper, Komossa, Kong, and Purves (2024) What’s in the news? A multiscalar text analysis approach to exploring news media discourses for managing protected areas in Switzerland. Landscape Research. DOI: https://doi.org/10.1080/01426397.2024.2358234The analysis is conducted as a geosemantic analysis as a part of ValPar.CH project.The archive contains 1) queries for corpus building at Swissdox@LiRI in YAML format, 2) intermediate data (i.e., topic modeling results), 3) markdown files for code lines both in html, pdf, and RMD.To be specific with the entailing dataset in the archive: 1) The corpus building for original text data was made of media data available via Swissdox@LiRI by the Linguistic Research Infrastructure of the University of Zurich (see https://t.uzh.ch/1hI for more information). The raw data required to reproduce the above findings cannot be openly shared due to commercial restrictions.2) However, the original query (in YAML format) used for retrieving data from Swissdox@LiRI can be found in .txt file attached.3) Additionally, aggregated/derived data are available to download from the folder attached.4) Statistics derived from the retrieved dataset(s) is available at the markdown files. <br><br>

本仓库用于存档Komossa、Kong与Purves(2024)发表于《景观研究(Landscape Research)》的论文《新闻中有何内容?探索瑞士保护区管理相关新闻媒体话语的多尺度文本分析方法》的分析流程,论文DOI:https://doi.org/10.1080/01426397.2024.2358234。本分析作为ValPar.CH项目的组成部分,采用地理语义学分析(geosemantic analysis)方法开展。 本存档包含以下内容:1)用于在Swissdox@LiRI平台构建语料库的YAML格式查询文件;2)中间数据(即主题建模(topic modeling)结果);3)包含代码行的markdown文件,可导出为HTML、PDF及RMD格式。 针对存档中的配套数据集,具体说明如下:1)原始文本数据的语料库构建基于苏黎世大学语言研究基础设施通过Swissdox@LiRI获取的媒体数据(详见https://t.uzh.ch/1hI)。因商业限制,复现该研究成果所需的原始数据无法公开共享。2)但用于从Swissdox@LiRI平台检索数据的原始查询文件(YAML格式)可在附件的.txt文件中获取。3)此外,聚合/衍生数据可通过附件文件夹下载。4)从检索数据集导出的统计数据可在markdown文件中查阅。
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figshare
创建时间:
2024-05-28
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