ArSarcasMoji Dataset: The Emoji Sentiment Roles in Arabic Ironic Contexts Article Swipe

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Emoji Irony Sarcasm Natural language processing Computer science Arabic Linguistics Artificial intelligence Sentiment analysis Modern Standard Arabic Social media World Wide Web Philosophy

Shatha Ali A. Hakami , Robert Hendley , Phillip Smith ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.18653/v1/2023.arabicnlp-1.18 · OA: W4389518212

In digital communication, emoji are essential in decoding nuances such as irony, sarcasm, and humour. However, their incorporation in Arabic natural language processing (NLP) has been cautious because of the perceived complexities of the Arabic language. This paper introduces ArSarcasMoji, a dataset of 24,630 emoji-augmented texts, with 17. 5% that shows irony. Through our analysis, we highlight specific emoji patterns paired with sentiment roles that denote irony in Arabic texts. The research counters prevailing notions, emphasising the importance of emoji’s role in understanding Arabic textual irony, and addresses their potential for accurate irony detection in Arabic digital content.