Facebook Reactions as Controversy Proxies: Predictive Models over Italian News

Discussion on social media over controversial topics can easily escalate to harsh interactions. Being able to predict whether a certain post will be controversial, and what reactions it might give rise to, could help moderators provide a better experience for all users. We develop a battery of dista...

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Autores principales:	Angelo Basile, Tommaso Caselli, Flavio Merenda, Malvina Nissim
Formato:	article
Lenguaje:	EN
Publicado:	Accademia University Press 2018
Materias:	Social Sciences H Computational linguistics. Natural language processing P98-98.5
Acceso en línea:	https://doaj.org/article/14545238b2ce416fa5799693fe1d6954
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spelling	oai:doaj.org-article:14545238b2ce416fa5799693fe1d69542021-12-02T09:52:23ZFacebook Reactions as Controversy Proxies: Predictive Models over Italian News2499-455310.4000/ijcol.514https://doaj.org/article/14545238b2ce416fa5799693fe1d69542018-12-01T00:00:00Zhttp://journals.openedition.org/ijcol/514https://doaj.org/toc/2499-4553Discussion on social media over controversial topics can easily escalate to harsh interactions. Being able to predict whether a certain post will be controversial, and what reactions it might give rise to, could help moderators provide a better experience for all users. We develop a battery of distant supervised models that use Facebook reactions as proxies for predicting news controversy, building on the idea that controversy can be modeled via the entropy of the reaction distribution to a post. We create a Facebook-based corpus for the study of controversy in Italian, and test on it the validity of our approach as well as a series of controversy models. Results show that controversy and reactions can be modelled successfully at various degrees of granularity.Angelo BasileTommaso CaselliFlavio MerendaMalvina NissimAccademia University PressarticleSocial SciencesHComputational linguistics. Natural language processingP98-98.5ENIJCoL, Vol 4, Iss 2, Pp 73-89 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Social Sciences H Computational linguistics. Natural language processing P98-98.5
spellingShingle	Social Sciences H Computational linguistics. Natural language processing P98-98.5 Angelo Basile Tommaso Caselli Flavio Merenda Malvina Nissim Facebook Reactions as Controversy Proxies: Predictive Models over Italian News
description	Discussion on social media over controversial topics can easily escalate to harsh interactions. Being able to predict whether a certain post will be controversial, and what reactions it might give rise to, could help moderators provide a better experience for all users. We develop a battery of distant supervised models that use Facebook reactions as proxies for predicting news controversy, building on the idea that controversy can be modeled via the entropy of the reaction distribution to a post. We create a Facebook-based corpus for the study of controversy in Italian, and test on it the validity of our approach as well as a series of controversy models. Results show that controversy and reactions can be modelled successfully at various degrees of granularity.
format	article
author	Angelo Basile Tommaso Caselli Flavio Merenda Malvina Nissim
author_facet	Angelo Basile Tommaso Caselli Flavio Merenda Malvina Nissim
author_sort	Angelo Basile
title	Facebook Reactions as Controversy Proxies: Predictive Models over Italian News
title_short	Facebook Reactions as Controversy Proxies: Predictive Models over Italian News
title_full	Facebook Reactions as Controversy Proxies: Predictive Models over Italian News
title_fullStr	Facebook Reactions as Controversy Proxies: Predictive Models over Italian News
title_full_unstemmed	Facebook Reactions as Controversy Proxies: Predictive Models over Italian News
title_sort	facebook reactions as controversy proxies: predictive models over italian news
publisher	Accademia University Press
publishDate	2018
url	https://doaj.org/article/14545238b2ce416fa5799693fe1d6954
work_keys_str_mv	AT angelobasile facebookreactionsascontroversyproxiespredictivemodelsoveritaliannews AT tommasocaselli facebookreactionsascontroversyproxiespredictivemodelsoveritaliannews AT flaviomerenda facebookreactionsascontroversyproxiespredictivemodelsoveritaliannews AT malvinanissim facebookreactionsascontroversyproxiespredictivemodelsoveritaliannews
_version_	1718397929723527168

Facebook Reactions as Controversy Proxies: Predictive Models over Italian News

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