id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_axzebh47qfh77lhyykpbcljizu	Dan Goldwasser	Understanding Satirical Articles Using Common-Sense	2016	14	.pdf	application/pdf	7859	813	60	into the satire detection task (Burfoot and Baldwin, 2009), predicting if a given news article is rather than looking at it as a lexical text classification task (Pang and Lee, 2008; Burfoot and Baldwin, 2009), which bases the decision on word-level Instead, we frame the required inferences as a highly-structured latent variable model, trained discriminatively as part of the The model learns commonsense patterns leading to real or satirical decisions The problem of building computational models dealing with humor, satire, irony and sarcasm has attracted considerable interest in the the Natural Language Processing (NLP) and Machine Learning inherently a common-sense reasoning task, as identifying the satirical aspects in narrative text does not inference process jointly assigning values to the latent variables and making the satire decision. Each node in the NRG is assigned a set of competing variables, mapping the node to different categories according to its type.	./cache/work_axzebh47qfh77lhyykpbcljizu.pdf	./txt/work_axzebh47qfh77lhyykpbcljizu.txt