解读衰落:对加拿大报纸二十年信息自由专栏的计算分析

IF 0.8 Q3 COMMUNICATION Canadian Journal of Communication Pub Date : 2022-05-09 DOI:10.22230/cjc.2022v47n2a4207
Alex Luscombe, Kevin Walby
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引用次数: 0

摘要

背景:报纸专栏文章是一种未被充分探索的传播模式,它涵盖了社会、文化和政治问题。分析:本文使用一种称为结构主题建模的无监督机器学习方法,绘制了加拿大报纸关于信息自由法的专栏文章语料库内容在20年期间的变化。这就有可能调查报纸专栏文章内容随时间的变化,并解读国家、地区和地方报纸发表的主题的趋势。结论和启示:使用计算方法分析新闻文本,并为未来信息自由和政治传播的研究提供建议。
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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Deciphering the Decline: A Computational Analysis of Two Decades of Canadian Newspaper Op-Eds on Freedom of Information
Background: Newspaper op-eds are an underexplored mode of communication that frame social, cultural, and political issues. Analysis: This article uses an unsupervised machine-learning approach called structural topic modelling to map changes in the content of a corpus of Canadian newspaper op-eds on freedom of information (FOI) law spanning a 20-year period. This makes it possible to investigate changes in the content of newspaper op-eds over time and to decipher trends in the kinds of topics that national, regional, and local newspapers publish. Conclusion and implications: Computational approaches to analyzing news texts are used, and recommendations are offered for future research on FOI and political communications.
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来源期刊
CiteScore
0.80
自引率
20.00%
发文量
51
期刊介绍: The objective of the Canadian Journal of Communication is to publish Canadian research and scholarship in the field of communication studies. In pursuing this objective, particular attention is paid to research that has a distinctive Canadian flavour by virtue of choice of topic or by drawing on the legacy of Canadian theory and research. The purview of the journal is the entire field of communication studies as practiced in Canada or with relevance to Canada. The Canadian Journal of Communication is a print and online quarterly. Back issues are accessible with a 12 month delay as Open Access with a CC-BY-NC-ND license. Access to the most recent year''s issues, including the current issue, requires a subscription. Subscribers now have access to all issues online from Volume 1, Issue 1 (1974) to the most recently published issue.
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