Supporting Emotion Automatic Detection and Analysis over Real-Life Text Corpora via Deep Learning: Model, Methodology, and Framework

Autor:	Giosuè Lo Bosco, Alfredo Cuzzocrea, Daniele Schicchi, Giovanni Pilato, Mariano Maiorana
Přispěvatelé:	Cuzzocrea, Alfredo, Lo Bosco, Giosuè, Maiorana, Mariano, Pilato, Giovanni, Schicchi, Daniele
Jazyk:	angličtina
Rok vydání:	2021
Předmět:	Text corpus Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni Settore INF/01 - Informatica Computer science business.industry Deep learning computer.software_genre NLP Deep Learning Artificial intelligence Satire Detection business computer Natural language processing
Popis:	This paper describes an approach for supporting automatic satire detection through effective deep learning (DL) architecture that has been shown to be useful for addressing sarcasm/irony detection problems. We both trained and tested the system exploiting articles derived from two important satiric blogs, Lercio and IlFattoQuotidiano, and significant Italian newspapers.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6a006dd8bd1ec0b42f0006fb7fa5975b http://hdl.handle.net/10447/519388 Zobrazit plný text záznamu