Sentiment analysis is an automatised technique of analysis aimed to measure the â polarityâ and the â subjectivityâ of large corpora of messages. The case study of the present paper consists of a selection of Pope Francisâ 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 â fact checkingâ seem not relevant to these forms of communication based on personal enunciation, on the relation between the two simulacra â meâ and â youâ , 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.

Enunciation and topic/comment structure: the offensive replies to Pope Francis' tweets, 2022-09-20.

Enunciation and topic/comment structure: the offensive replies to Pope Francis' tweets

Francesco Galofaro
;
2022-09-20

Abstract

Sentiment analysis is an automatised technique of analysis aimed to measure the â polarityâ and the â subjectivityâ of large corpora of messages. The case study of the present paper consists of a selection of Pope Francisâ 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 â fact checkingâ seem not relevant to these forms of communication based on personal enunciation, on the relation between the two simulacra â meâ and â youâ , 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.
Inglese
http://rifl.unical.it/index.php/rifl/article/view/714
SFL2021
243
253
10
internazionale
esperti anonimi
A stampa
Settore M-FIL/05 - Filosofia e Teoria dei Linguaggi
Horizon2020
757314
2
File in questo prodotto:
File Dimensione Formato  
RIFL_QUANTUM_REPLIES_TWITTER.pdf

Open Access

Tipologia: Documento in Post-print
Dimensione 720.3 kB
Formato Adobe PDF
720.3 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10808/47004
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • ???jsp.display-item.citation.isi??? ND
social impact