Painting the Senate# Green: A Corpus Study of Twitter Sentiment Towards the Italian Environmentalist Blitz1
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Painting the Senate# Green: A Corpus Study of Twitter Sentiment Towards the Italian Environmentalist Blitz1
Original language description
"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"
Czech name
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Czech description
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Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
"Proceedings of the International Conference “Dialogue 2023”"
ISSN
2221-7932
e-ISSN
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Volume of the periodical
""
Issue of the periodical within the volume
2023
Country of publishing house
US - UNITED STATES
Number of pages
11
Pages from-to
1-11
UT code for WoS article
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EID of the result in the Scopus database
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