Painting the Senate# Green: A Corpus Study of Twitter Sentiment Towards the Italian Environmentalist Blitz1
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AXPN77A7A" target="_blank" >RIV/00216208:11320/23:XPN77A7A - isvavai.cz</a>
Výsledek na webu
<a href="https://www.dialog-21.ru/media/5868/biancoaplusetal045.pdf" target="_blank" >https://www.dialog-21.ru/media/5868/biancoaplusetal045.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.28995/2075-7182-2023-22-1021-1031" target="_blank" >10.28995/2075-7182-2023-22-1021-1031</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Painting the Senate# Green: A Corpus Study of Twitter Sentiment Towards the Italian Environmentalist Blitz1
Popis výsledku v původním jazyce
"Painting the Senate #Green: A Corpus Study of Twitter SentimentnTowards the Italian Environmentalist Blitz 1nAntonio BianconUniversity ofnBergamo/PavianPiazza del Lino, 2, 27100nPavia (PV), Italynantonio.bianco@unibg.itnClaudia Roberta CombeinUniversity of PavianPiazza del Lino, 2, 27100nPavia (PV), Italynclaudiaroberta.combei@unipv.itnChiara ZanchinUniversity of PavianPiazza del Lino, 2, 27100nPavia (PV), Italynchiara.zanchi01@unipv.itnAbstractnThis study analyzes the reactions of the Italian Twitter community to an environmental demonstration that occurred in Romenon January 2 nd, 2023. We compiled a corpus of 368,531 tokens consisting of 11,780 tweets, collected during a 7-day period.nWe propose a mixed-method approach that combines automated and manual corpus analyses of sentiment, emotions, andnimplicit language. Our findings offer insights into how tweets reflected the users’ attitudes toward a variety of subjects andnentities. Although the sentiment of the overall debate was distributed rather evenly, the incident itself seems to have sparkednnegative sentiment and emotions among Twitter users. The results of our manual analyses revealed some issues with respectnto the automatic classification of sentiment, due to the fact that some tweets contained irony, sarcasm, and slurs. Non-literalninterpretations were ignored by the tools at hand that could not account for complex rhetorical-argumentative strategies"
Název v anglickém jazyce
Painting the Senate# Green: A Corpus Study of Twitter Sentiment Towards the Italian Environmentalist Blitz1
Popis výsledku anglicky
"Painting the Senate #Green: A Corpus Study of Twitter SentimentnTowards the Italian Environmentalist Blitz 1nAntonio BianconUniversity ofnBergamo/PavianPiazza del Lino, 2, 27100nPavia (PV), Italynantonio.bianco@unibg.itnClaudia Roberta CombeinUniversity of PavianPiazza del Lino, 2, 27100nPavia (PV), Italynclaudiaroberta.combei@unipv.itnChiara ZanchinUniversity of PavianPiazza del Lino, 2, 27100nPavia (PV), Italynchiara.zanchi01@unipv.itnAbstractnThis study analyzes the reactions of the Italian Twitter community to an environmental demonstration that occurred in Romenon January 2 nd, 2023. We compiled a corpus of 368,531 tokens consisting of 11,780 tweets, collected during a 7-day period.nWe propose a mixed-method approach that combines automated and manual corpus analyses of sentiment, emotions, andnimplicit language. Our findings offer insights into how tweets reflected the users’ attitudes toward a variety of subjects andnentities. Although the sentiment of the overall debate was distributed rather evenly, the incident itself seems to have sparkednnegative sentiment and emotions among Twitter users. The results of our manual analyses revealed some issues with respectnto the automatic classification of sentiment, due to the fact that some tweets contained irony, sarcasm, and slurs. Non-literalninterpretations were ignored by the tools at hand that could not account for complex rhetorical-argumentative strategies"
Klasifikace
Druh
J<sub>ost</sub> - Ostatní články v recenzovaných periodicích
CEP obor
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OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
—
Návaznosti
—
Ostatní
Rok uplatnění
2023
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
"Proceedings of the International Conference “Dialogue 2023”"
ISSN
2221-7932
e-ISSN
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Svazek periodika
""
Číslo periodika v rámci svazku
2023
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
11
Strana od-do
1-11
Kód UT WoS článku
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EID výsledku v databázi Scopus
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