Automatic social media news classification: a topic modeling approach
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Авторы: | , , , |
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Формат: | artículo original |
Статус: | Versión publicada |
Дата публикации: | 2022 |
Описание: | 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. |
Страна: | RepositorioTEC |
Институт: | Instituto Tecnológico de Costa Rica |
Repositorio: | RepositorioTEC |
Язык: | Inglés Español |
OAI Identifier: | oai:repositoriotec.tec.ac.cr:2238/14160 |
Online-ссылка: | https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/6477 https://hdl.handle.net/2238/14160 |
Access Level: | acceso abierto |
Ключевое слово: | Automatic news classification social media topic modeling Clasificación automática de noticias Modelado de tópicos Redes sociales |