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001-es BibID:	BIBFORM107046
035-os BibID:	(Scopus)85067408475
Első szerző:	Abdelzaher, Esra (linguist)
Cím:	Lexicon-based Detection of Violence on Social Media / Abdelzaher, Esra' M.
Dátum:	2019
ISSN:	2352-6416
Megjegyzések:	This study adopts a lexicon-based approach to address violence on social media. It uses FrameNet 1.7 (fn) and WordNet 3.1 (wn) to build a hierarchical domain-specific language resource of violence. The proposed lexicon tethers fn's innovative integration of linguistic and paralinguistic knowledge to wn's hierarchically-organized database. This tether alleviates the need to gather all paralinguistic violence-associated scenes and organize their linguistic realizations hierarchically. The proposed methodology can be internationally applied, given the multilingual availability of fn and wn, to cognitively and quantitatively explore a concept or a phenomenon. The lexicon is applied, then, to a corpus representing posts and comments retrieved from Donald Trump's Facebook public page. Results reveal that the proposed lexicon recalls 92.68 of the total violence-related words in the corpus with a 76.31 precision (F-score=83.7). More important, relating wn to fn inspires the creation of new frames, suggests slight modifications to existing ones and advocates promising mapping between some frames and synsets.
Tárgyszavak:	Bölcsészettudományok Nyelvtudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk frame semantics FrameNet language resource social media violence
Megjelenés:	Cognitive Semantics. - 5 : 1 (2019), p. 32-69. -
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