| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560334 |
| ISSN: | 1405-5546 |
| Autors: | Daouadi, Kheir Eddine1 Rebaï, Rim Zghal2 Amous, Ikram2 |
| Institucions: | 1Sfax University, Faculty of Economics and Management of Sfax, Sfax. Túnez 2Sfax University, Higher Institute of Computer Science and Multimedia of Sfax, Sfax. Túnez |
| Any: | 2019 |
| Període: | Abr-Jun |
| Volum: | 23 |
| Número: | 2 |
| Paginació: | 273-279 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Resumen en inglés | Today, through Twitter, researchers propose approaches for classifying user accounts. However, they have to face confidence challenges owing to the diversity of the types of data propagated throughout Twitter. In addition, the messages from Twitter are imprecise, very short and even written in many dialects and languages. Moreover, the majority of the related works focus on the overall user's activity, which makes them not suitable at the post-level classification. This paper presents an alternative approach for classifying user accounts as being accounts of bots, humans or organizations. The suggested approach consists in accurately classifying user accounts from one single post by leveraging a minimal number of language-independent features. We performed several experiments over a Twitter datasets and supervised learn-based algorithms. Our results demonstrated that simply using a minimal number of language-independent features extracted from one single post is sufficient to classify user accounts accurately and quickly. Our proposed approach yielded high F1-measure (>95%) and high AUC (>99%) using Random Forest. |
| Disciplines | Ciencias de la computación |
| Paraules clau: | Inteligencia artificial |
| Keyword: | Social network analysis, Twitter user classification, Human vs. bot vs. organization, Statistical-based approach, Content-based approach, Hybrid-based approach, Artificial intelligence |
| Text complet: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
