Automatic social media news classification: a topic modeling approach

 

Đã lưu trong:
Chi tiết về thư mục
Nhiều tác giả: Amador, Daniel, Gamboa-Venegas, Carlos, García, Ernesto, Segura-Castillo, Andrés
Định dạng: artículo original
Trạng thái:Versión publicada
Ngày xuất bản:2022
Miêu tả: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.
Quốc gia:Portal de Revistas TEC
Tổ chức giáo dục:Instituto Tecnológico de Costa Rica
Repositorio:Portal de Revistas TEC
Ngôn ngữ:Inglés
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OAI Identifier:oai:ojs.pkp.sfu.ca:article/6477
Truy cập trực tuyến:https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/6477
Từ khóa:Automatic news classification
social media
topic modeling
Clasificación automática de noticias
Modelado de tópicos
Redes sociales