Detection of Hate Speech Spreaders with BERT (CROSBI ID 708207)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Dukić, David ; Sović Kržić, Ana
engleski
Detection of Hate Speech Spreaders with BERT
As social media grows, more and more users are disseminating hate speech through their posts. This often comes as a consequence of feeling a false security and anonymity in virtual environment. To stop hate speech spreaders, researchers started developing machine learning systems that automatically detect spreaders of hate speech based on the contents of their posts. This paper describes one such system which was trained on a corpus of English Twitter posts with a goal to predict if author of the given posts spreads hate speech or not. The features were crafted using fine-tuned BERT contextualized embeddings summed over the last 12 hidden states corresponding to the classification token, concatenated with the three binary variables called indicators. Binary variables were indicating whether hashtag, retweet or url were present in author's tweet posts, respectively. Feature vectors were then fed into a Logistic Regression classifier. Described model achieved 75% of accuracy score on the test set.
BERT ; fine-tuning ; indicators ; logistic regression
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Podaci o prilogu
1-10.
2021.
objavljeno
Podaci o matičnoj publikaciji
CLEF 2021 Labs and Workshops, Notebook Papers
Faggioli, Guglielmo ; Ferro, Nicola ; Joly, Alexis ; Maistro, Maria ; Piroi, Florina
Bukurešt:
1613-0073
Podaci o skupu
CLEF 2021
radionica
21.09.2021-24.09.2021
Bukurešt, Rumunjska