Monitoring Social Media to Identify Environmental Crimes through NLP A Preliminary Study
| Autor: | Antonio Pascucci, Vincenzo Simoniello, Johanna Monti, Wanda Punzi Zarino, Raffaele Manna |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
UNIOR Eye corpus
Computer science AriEmozione Online Hate Speech CBX Multilingual NLU Social media Twitter during Pandemic Automatic Sarcasm Detection Linguistic Ostracism in Social Networks COVID-19 Linguistics LAN000000 Data science Quantitative Linguistic Investigations environmental crimes Fine-grained sentiment analysis Computational Linguistics DistilBERT Depression from Social Media Distributional Semantics Gender Bias UNIOR Eye corpus environmental crimes AEREST E3C Project TrAVaSI |
| Zdroj: | CLiC-it |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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