Sentiment analysis is an automatised technique of analysis aimed to measure the “polarity” and the “subjectivity” of large corpora of messages. The case study of the present paper consists of a selection of Pope Francis’ tweets on ecological, social, religious themes and the relative polemic replies. In the degree of agreement/disagreement in response to a tweet, the referential function is not relevant; the emotive and conative functions prevail. The political strategies aimed at corroborating or refuting claims in terms of “fact checking” seem not relevant to these forms of communication based on personal enunciation, on the relation between the two simulacra “me” and “you”, and on the manifestation of one's own comment with respect to a topic. Furthermore, the techniques aimed at detecting the presence of hate speeches to apply, possibly, a precautionary censorship are lexical-sensitive, and fail to consider the context in which words co-occur. Finally, the paper presents a technique of analysis based on quantum information retrieval which can provide new insights on the relation between hashtag, address sign, topic, and reply.

Enunciationand topic/comment structure: the offensive replies to Pope Francis’ tweets

Francesco Galofaro
;
Zeno Toffano
2022-01-01

Abstract

Sentiment analysis is an automatised technique of analysis aimed to measure the “polarity” and the “subjectivity” of large corpora of messages. The case study of the present paper consists of a selection of Pope Francis’ tweets on ecological, social, religious themes and the relative polemic replies. In the degree of agreement/disagreement in response to a tweet, the referential function is not relevant; the emotive and conative functions prevail. The political strategies aimed at corroborating or refuting claims in terms of “fact checking” seem not relevant to these forms of communication based on personal enunciation, on the relation between the two simulacra “me” and “you”, and on the manifestation of one's own comment with respect to a topic. Furthermore, the techniques aimed at detecting the presence of hate speeches to apply, possibly, a precautionary censorship are lexical-sensitive, and fail to consider the context in which words co-occur. Finally, the paper presents a technique of analysis based on quantum information retrieval which can provide new insights on the relation between hashtag, address sign, topic, and reply.
Campo DC Valore Lingua
dc.authority.ancejournal RIVISTA ITALIANA DI FILOSOFIA DEL LINGUAGGIO en
dc.authority.people Francesco Galofaro en
dc.authority.people Zeno Toffano en
dc.authority.project 757314 en
dc.collection.id.s e27ce441-d6cc-2581-e053-d805fe0acbaa *
dc.collection.name 03A-Articolo su Rivista *
dc.contributor.appartenenza FILOSOFIA E SCIENZE DELL'EDUCAZIONE *
dc.contributor.appartenenza.mi 514 *
dc.contributor.country FRA en
dc.date.accessioned 2022-09-20T10:06:20Z -
dc.date.available 2022-09-20T10:06:20Z -
dc.date.firstsubmission 2022-09-20T10:06:20Z *
dc.date.issued 2022 -
dc.date.submission 2022-09-20T10:06:20Z *
dc.description.abstract Sentiment analysis is an automatised technique of analysis aimed to measure the “polarity” and the “subjectivity” of large corpora of messages. The case study of the present paper consists of a selection of Pope Francis’ tweets on ecological, social, religious themes and the relative polemic replies. In the degree of agreement/disagreement in response to a tweet, the referential function is not relevant; the emotive and conative functions prevail. The political strategies aimed at corroborating or refuting claims in terms of “fact checking” seem not relevant to these forms of communication based on personal enunciation, on the relation between the two simulacra “me” and “you”, and on the manifestation of one's own comment with respect to a topic. Furthermore, the techniques aimed at detecting the presence of hate speeches to apply, possibly, a precautionary censorship are lexical-sensitive, and fail to consider the context in which words co-occur. Finally, the paper presents a technique of analysis based on quantum information retrieval which can provide new insights on the relation between hashtag, address sign, topic, and reply. en
dc.description.allpeople Francesco Galofaro; Zeno Toffano -
dc.description.allpeopleoriginal Francesco Galofaro; Zeno Toffano en
dc.description.fulltext open en
dc.description.international si en
dc.description.numberofauthors 2 -
dc.fulltext.apc NO en
dc.fulltext.oa 1 – prodotto con file in versione Open Access (allegherò il file al passo 5-Carica) en
dc.identifier.doi 10.4396/SFL2021A23 en
dc.identifier.source manual *
dc.identifier.uri http://hdl.handle.net/2318/1874494 -
dc.identifier.url http://rifl.unical.it/index.php/rifl/article/view/714 en
dc.language.iso eng en
dc.relation.firstpage 243 en
dc.relation.lastpage 253 en
dc.relation.numberofpages 11 en
dc.relation.projectAcronym NeMoSanctI en
dc.relation.projectAwardNumber - en
dc.relation.projectAwardTitle - en
dc.relation.projectFunderName - en
dc.relation.projectFundingStream H2020 en
dc.relation.volume SFL2021 en
dc.subject.keywords semiotics, quantum semantics, information retrieval, machine learning, sentiment analysis, hate speech, conspiracy theory. en
dc.subject.singlekeyword semiotics *
dc.subject.singlekeyword quantum semantics *
dc.subject.singlekeyword information retrieval *
dc.subject.singlekeyword machine learning *
dc.subject.singlekeyword sentiment analysis *
dc.subject.singlekeyword hate speech *
dc.subject.singlekeyword conspiracy theory *
dc.title Enunciationand topic/comment structure: the offensive replies to Pope Francis’ tweets en
dc.type.driver info:eu-repo/semantics/article -
dc.type.full 03-CONTRIBUTO IN RIVISTA::03A-Articolo su Rivista it
dc.type.miur 262 -
dc.type.referee Esperti anonimi en
dc.ugov.classprodaux M-FIL/05 - FILOSOFIA E TEORIA DEI LINGUAGGI en
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