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 …

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 …

For a long time, figurative language was studied merely from linguistic perspectives, yet it
has lately captured the attention of other fields, such as natural language processing …

Sarcasm is one of the main challenges for sentiment analysis systems. Its complexity comes
from the expression of opinion using implicit indirect phrasing. In this paper, we present …

This paper provides an overview of the WANLP 2021 shared task on sarcasm and sentiment
detection in Arabic. The shared task has two subtasks: sarcasm detection (subtask 1) and …

As the use of automated social media analysis tools surges, concerns over accuracy of
analytics have increased. Some tentative evidence suggests that sarcasm alone could …

We consider the distinction between intended and perceived sarcasm in the context of
textual sarcasm detection. The former occurs when an utterance is sarcastic from the …

Sarcasm is sophisticated linguistic expression and is commonly observed on social media
and e-commerce platforms. Failure to detect sarcastic expressions in natural language …

Irony detection in social networks has drawn much attention in recent years. In this work, we
propose a three-way decisions based feature fusion method for Chinese irony detection in …

Data annotation is the foundation of most natural language processing (NLP) tasks.
However, data annotation is complex and there is often no specific correct label, especially …