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| Main Author: | |
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| Format: | Artículo científico |
| Language: | en |
| Published: |
Instituto Politécnico Nacional
2017
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| Subjects: | |
| Online Access: | https://www.redalyc.org/articulo.oa?id=61553900013 |
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Table of Contents:
- A Supervised Method to Predict the Popularity of News Articles Ali Balali Masoud Asadpour Hesham Faili Computación Text mining social media user behavior comments volume content popularity 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 a pproach 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 improv ement in comparison with the baseline methods. 2017 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61553900013 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.4 Vol.21