Automated Detection of Bilingual Obfuscated Abusive Words on Social Media Forums: A Case of Swahili and English Texts

Abstract

The usage of social media has exponentially grown in recent years leaving the users with no limitations on misusing the platforms through abusive contents as deemed fit to them. This exacerbates abusive words exposure to innocent users, especially in social media forums, including children. In an attempt to alleviate the problem of abusive words proliferation on social media, researchers have proposed different methods to help deal with variants of the abusive words; however, obfuscated abusive words detection still poses challenges. A method that utilizes a combination of rule based approach and character percentage matching techniques is proposed to improve the detection rate for obfuscated abusive words. The evaluation results achieved F1 score percentage ratio of 0.97 and accuracy percentage ratio of 0.96 which were above the significance ratio of 0.5. Hence, the proposed approach is highly effective for obfuscated abusive words detection and prevention.

Keywords:     Rule based approach, Character percentage matching techniques, Obfuscated abuse, Abuse detection, Abusive words, Social media