Name
Abstract | ||
|---|---|---|
Social media platforms have been increasingly used by modern society. In most platforms, users usually share content on various subjects and, in particular, politics is a favorite one. There are many interests in detecting and analyzing such a political content. However, there is a challenge in the process of detecting specific subjects from social media data mainly due to its informality. In this paper, we propose and compare two techniques, based on supervised classification, for the detection of tweets with political content. The results obtained by our approach have demonstrated satisfactory performance, which motivates further research to be undertaken. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3243082.3243113 | WEBMEDIA'18: PROCEEDINGS OF THE 24TH BRAZILIAN SYMPOSIUM ON MULTIMEDIA AND THE WEB |
Keywords | Field | DocType |
Machine learning, Deep learning, Logistic regression, Social networks analysis, Text mining | Data science,Social media,Computer science,Artificial intelligence,Deep learning,Multimedia,Politics | Conference |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Brunna de Sousa Pereira Amorim | 1 | 0 | 1.01 |
| André Luiz Firmino Alves | 2 | 9 | 2.94 |
| Maxwell Guimarães de Oliveira | 3 | 24 | 7.15 |
| Cláudio de Souza Baptista | 4 | 133 | 31.73 |