| Journal: | Computación y Sistemas |
| Database: | PERIÓDICA |
| System number: | 000423298 |
| ISSN: | 1405-5546 |
| Authors: | Balali, Ali1 Asadpour, Masoud1 Faili, Hesham1 |
| Institutions: | 1University of Tehran, College of Engineering, Teherán. Irán |
| Year: | 2017 |
| 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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