This overview paper describes the first shared task on irony detection for the Arabic
language. The task consists of a binary classification of tweets as ironic or not using a …

Language models are ubiquitous in current NLP, and their multilingual capacity has recently
attracted considerable attention. However, current analyses have almost exclusively focused …

In the last decade, the need to detect automatically irony to correctly recognize the sentiment
and hate speech involved in online texts increased the investigation on humorous figures of …

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 …

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 …

This paper introduces IroSvA, the first shared task fully dedicated to identify the presence of
irony in short messages (tweets and news comments) written in three different variants of …

Making machines understand language and reasoning on it has been one of the most
challenging problems addressed by Artificial Intelligent researchers. This challenge …

This paper proposes the first multilingual (French, English and Arabic) and multicultural
(Indo-European languages vs. less culturally close languages) irony detection system. We …

This paper presents an in-depth investigation of the effectiveness of dependency-based
syntactic features on the irony detection task in a multilingual perspective (English, Spanish …

Embeddings are very popular representations that allow computing semantic and syntactic
similarities between linguistic units from text co-occurrence matrix. Units can vary from …