id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-020830-97xmu329	Ghanem, Bilal	Irony Detection in a Multilingual Context	2020-03-24		.txt	text/plain	2806	158	54	We show that these monolingual models trained separately on different languages using multilingual word representation or text-based features can open the door to irony detection in languages that lack of annotated data for irony. We aim here to bridge the gap by tackling ID in tweets from both multilingual (French, English and Arabic) and multicultural perspectives (Indo-European languages whose speakers share quite the same cultural background vs. We can justify that by, the language presentation of the Arabic and French tweets are quite informal and have many dialect words that may not exist in the pretrained embeddings we used comparing to the English ones (lower embeddings coverage ratio), which become harder for the CNN to learn a clear semantic pattern. The CNN architecture trained on cross-lingual word representation shows that irony has a certain similarity between the languages we targeted despite the cultural differences which confirm that irony is a universal phenomena, as already shown in previous linguistic studies [9, 24, 35] .	./cache/cord-020830-97xmu329.txt	./txt/cord-020830-97xmu329.txt