The growing prevalence and rapid evolution of offensive language in social media amplify
the complexities of detection, particularly highlighting the challenges in identifying such …

The prevalence of offensive content on online communication and social media platforms is
growing more and more common, which makes its detection difficult, especially in …

The growth of social networks has provided a platform for individuals with prejudiced views,
allowing them to spread hate speech and target others based on their gender, ethnicity …

The rise of social media has enabled individuals with biased perspectives to spread hate
speech, directing it toward individuals based on characteristics such as race, gender …

Numerous attempts have been made to address Aspect-based Sentiment Analysis (ABSA),
with a predominant emphasis on English texts. Tackling ABSA in low-resource languages …

The rapid proliferation of hate speech on social media poses significant challenges to
maintaining a safe and inclusive digital environment. This paper presents a comprehensive …

Most research on hate speech detection has focused on English where a sizeable amount of
labeled training data is available. However, to expand hate speech detection into more …

Hate speech in social media is a growing issue nowadays that negatively affects the society
and individuals within. Moreover, hate speech detection is a challenging task, due to the …

The rapid growth of social media platforms has led to an increase in hate speech. This has
prompted the development of effective detection mechanisms that aim to mitigate the …

Aspect-based sentiment analysis (ABSA) is a sequence labeling task that has garnered
growing research interest in multilingual contexts. However, recent studies lack more robust …