社交媒体新闻自动分类:一种主题建模方法

IF 0.1 Q4 MULTIDISCIPLINARY SCIENCES
Daniel Amador, Carlos Gamboa-Venegas, Ernesto García, Andrés Segura-Castillo
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引用次数: 0

摘要

社交媒体改变了人们获取新闻和讨论公共问题的方式。虽然可以将访问大量数据源视为一种优势,但随着内容合法性和真实性问题开始在用户中流行,一些新的挑战也出现了。公共领域的这种转变催生了错误信息和假新闻等问题。要了解正在发布的信息类型,可以使用计算工具对新闻进行自动分类。因此,这篇短文提出了一个检索和分析新闻的平台,以及使用主题建模方法对新闻进行自动分类的有希望的结果,这应该有助于受众更容易地识别新闻内容,并讨论在不久的将来改善这种情况的可能途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic social media news classification: a topic modeling approach
Social media has modified the way that people access news and debate about public issues. Although access to a myriad of data sources can be considered an advantage, some new challenges have emerged, as issues about content legitimacy and veracity start to prevail among users. That transformation of the public sphere propels problematic situations, such as misinformation and fake news. To understand what type of information is being published, it is possible to categorize news automatically using computational tools. Thereby, this short paper presents a platform to retrieve and analyze news, along with promising results towards automatic news classification using a topic modeling approach, which should help audiences to identify news content easier and discusses possible routes to improve the situation in the near future.
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来源期刊
Tecnologia en Marcha
Tecnologia en Marcha MULTIDISCIPLINARY SCIENCES-
自引率
0.00%
发文量
93
审稿时长
28 weeks
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