Online toxic discourses could result in conflicts between groups or harm to online
communities. Hate speech is complex and multifaceted harmful or offensive content …

The use of online social networks has made significant progress in recent years as the use
of the Internet has become widespread worldwide as the technological infrastructure and the …

Sarcasm identification on text documents is one of the most challenging tasks in natural
language processing (NLP), has become an essential research direction, due to its …

Misinformation about the COVID-19 pandemic proliferated widely on social media platforms
during the course of the health crisis. Experts have speculated that consuming …

Abstract iSarcasmEval is the first shared task to target intended sarcasm detection: the data
for this task was provided and labelled by the authors of the texts themselves. Such an …

The proliferation of social media enables people to express their opinions widely online.
However, at the same time, this has resulted in the emergence of conflict and hate, making …

Social stereotypes negatively impact individuals' judgments about different groups and may
have a critical role in understanding language directed toward marginalized groups. Here …

Figurative language (FL) seems ubiquitous in all social media discussion forums and chats,
posing extra challenges to sentiment analysis endeavors. Identification of FL schemas in …

Automatic sarcasm detection is the task of predicting sarcasm in text. This is a crucial step to
sentiment analysis, considering prevalence and challenges of sarcasm in sentiment-bearing …

Sarcasm is often expressed through several verbal and non-verbal cues, eg, a change of
tone, overemphasis in a word, a drawn-out syllable, or a straight looking face. Most of the …