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3 septembre 2021
- doi: 10.4000/books.aaccademia.8675
- eisbn: 9791280136336
https://www.openedition.org/12554 , info:eu-repo/semantics/openAccess
Mots-clés
Computational Linguistics Fine-grained sentiment analysis Distributional Semantics Quantitative Linguistic Investigations Gender Bias Depression from Social Media Online Hate Speech Automatic Sarcasm Detection TrAVaSI AriEmozione AEREST COVID-19 Linguistic Ostracism in Social Networks Multilingual NLU E3C Project DistilBERT Twitter during Pandemic LAN000000 Linguistics CBXSujets proches
Offenses, Environmental Environmental crimes Offenses, Pollution Environmental offenses Crimes against the environment Pollution offenses Pollution crimes User-generated mediaCiter ce document
Raffaele Manna et al., « Monitoring Social Media to Identify Environmental Crimes through NLP A Preliminary Study », Accademia University Press, ID : 10.4000/books.aaccademia.8675
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Résumé
This paper presents the results of research carried out on the UNIOR Eye corpus, a corpus which has been built by downloading tweets related to environmental crimes. The corpus is made up of 228,412 tweets organized into four different subsections, each one concerning a specific environmental crime. For the current study we focused on the subsection of waste crimes, composed of 86,206 tweets which were tagged according to the two labels alert and no alert. The aim is to build a model able to detect which class a tweet belongs to.