Cyberbullying Detection in Roman Urdulanguage Using Lexicon Based Approach
Year: 2020
Type: article
Abstract: Nowadays, online social networks (OSNs) have become integral part of our daily life and online
users of social media are massively growing. The increasing use of OSNs by users leads to large amount of user
communication data. This study focuses on OSNs users who communicate in Roman Urdu (Urdu language
written in English alphabets). Pakistan alone has over 44 million OSNs users who communicate in Roman Urdu.
In this paper, we addressed the issue of cyberbullying behavior on Twitter platform, where users use Roman
Urdu as medium of their communication. To the best of our knowledge, this is the first study addressing
cyberbullying behavior in Roman Urdu. To address this issue, we developed supervised machine learning
method and proposed a lexicon-based model with set of features derived from Twitter. An evaluation model
shows that the developed model attained results with area under receiver operating characteristics curve (AUC)
of 0.986 and f-measure of 0.984. These results indicate that the proposed lexicon-based method gives feasible
solution for detecting cyberbullying behavior in Roman Urdu in OSNs. Finally, we compared results achieved
with our proposed lexicon-based method and the results obtained from other well-known models. The
comparison results show the significance of our proposed model.
Source: Journal of Critical Reviews
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W3039058964