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Analiza sentimenta novinskih članaka vezanih za tematiku koronavirusa

Sentiment analysis of coronavirus related news
Authors: Ilić, Anton;

Analiza sentimenta novinskih članaka vezanih za tematiku koronavirusa

Abstract

In early 2020, a pandemic of the novel coronavirus SARS-Cov-2 spread to the entire world and its impact changed our ways of life in a social and digital sense. The aim of this paper is to determine the impact of the pandemic on media reporting and to measure the emotional impact of this reporting on readers through programmatic methods of sentiment analysis. For this purpose, the whole process of opinion mining is presented which includes the phase of automated data collection and structuring, through to their processing and analysis. The analysis phase presents the basics of statistical observations from the collected data and their interpretation in the context of the pandemic and the nature of human opinion in a negative and non-negative sense. Furthermore, the paper demonstrates the work and compares the efficiency of using conventional linguistic methods with more modern approaches based on artificial intelligence.

Početkom 2020. godine, pandemija novog koronavirusa SARS-Cov-2 je zahvatila cijeli svijet te svojim utjecajem promijenila naše načine života u društvenom i digitalnom smislu. Cilj ovog rada je utvrditi utjecaj pandemije na medijsko izvještavanje te izmjeriti emocionalni utjecaj tog izvještavanja na čitatelje programskim putem metodama analize sentimenta. U tu svrhu je prikazan cijeli postupak rudarenja mišljenja od faze automatiziranog prikupljanja i strukturiranja podataka, do njihove obrade i analize. U fazi analize su prikazane osnove statističkih opažanja iz prikupljenih podataka te njihova interpretacija u kontekstu pandemije i naravi ljudskog mišljenja u negativnom i ne-negativnom smislu. Nadalje u radu je demonstriran rad i provedena usporedba efikasnosti korištenja konvencionalnih lingvističkih metoda s modernijim pristupima baziranih na umjetnoj inteligenciji.

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Keywords

analiza sentimenta ; COVID-19 ; novinski portal ; online vijesti ; Python ; strojno učenje ; nenadzirano učenje

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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