A Supervised Method to Predict the Popularity of News Articles



Document title: A Supervised Method to Predict the Popularity of News Articles
Journal: Computación y Sistemas
Database: PERIÓDICA
System number: 000423298
ISSN: 1405-5546
Authors: 1
1
1
Institutions: 1University of Tehran, College of Engineering, Teherán. Irán
Year:
Season: Oct-Dic
Volumen: 21
Number: 4
Country: México
Language: Inglés
Document type: Artículo
Approach: Analítico, descriptivo
English abstract In this study, we identify the features of an article that encourage people to leave a comment for it. The volume of the received comments for a news article shows its importance. It also indirectly indicates the amount of influence a news article has on the public. Leaving comment on a news article indicates not only the visitor has read the article but also the article has been important to him/her. We propose a machine learning approach to predict the volume of comments using the information that is extracted about the users’ activities on the web pages of news agencies. In order to evaluate the proposed method, several experiments were performed. The results reveal salient improvement in comparison with the baseline methods
Disciplines: Ciencias de la computación,
Literatura y lingüística
Keyword: Lingüística aplicada,
Minería de texto,
Noticias,
Usuarios de la información
Keyword: Applied linguistics,
Text mining,
News,
Information users
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