Name
Abstract | ||
|---|---|---|
The massive use of the social media and the huge number of messages that are shared on the internet, create a countless need to automatically detect the age and gender of the people who write these messages. Several sites and platforms attempt to mislead and cheat the people who are visiting them by providing deceptive information about the age and the gender of their customer. The traditional way to detect deceivers was by human judgment, but this way is no longer suitable since lots of interviews are not conducted face to face. This paper presents an automate tool with a unique set of features that used to analyze a given text. The features include the unigram, part of speech, and production rules. The accuracy results of the proposed method outperform the existing techniques. The best results achieved by using the production rules features. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.procs.2020.03.126 | Procedia Computer Science |
Keywords | DocType | Volume |
Open domain text,Deceptive information,Age prediction,Gender prediction | Conference | 170 |
ISSN | Citations | PageRank |
1877-0509 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emad E. Abdallah | 1 | 112 | 12.57 |
| Jamil R. Alzghoul | 2 | 0 | 0.34 |
| Muath Alzghool | 3 | 26 | 4.64 |