2020 ◽  
Vol 3 (2) ◽  
pp. 279-317 ◽  
Author(s):  
Shadi Shahsavari ◽  
Pavan Holur ◽  
Tianyi Wang ◽  
Timothy R. Tangherlini ◽  
Vwani Roychowdhury

2019 ◽  
Author(s):  
ulio Cesar Amador Diaz Lopez ◽  
Miguel Molina-Solana ◽  
Juan Gomez Romero

2017 ◽  
Vol 15 (3) ◽  
pp. 219-231 ◽  
Author(s):  
Zaher Yamak ◽  
Julien Saunier ◽  
Laurent Vercouter

2019 ◽  
Vol 52 (10) ◽  
pp. 1150-1156 ◽  
Author(s):  
Hao Yan ◽  
Ellen E. Fitzsimmons‐Craft ◽  
Micah Goodman ◽  
Melissa Krauss ◽  
Sanmay Das ◽  
...  

2021 ◽  
Vol 1911 (1) ◽  
pp. 012012
Author(s):  
R Geetha ◽  
S Karthika ◽  
Chaluvadi Jwala Sowmika ◽  
Bharathi M Janani

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 213154-213167
Author(s):  
Giuseppe Sansonetti ◽  
Fabio Gasparetti ◽  
Giuseppe D'aniello ◽  
Alessandro Micarelli

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Nauman Ul Haq ◽  
Mohib Ullah ◽  
Rafiullah Khan ◽  
Arshad Ahmad ◽  
Ahmad Almogren ◽  
...  

The use of slang, abusive, and offensive language has become common practice on social media. Even though social media companies have censorship polices for slang, abusive, vulgar, and offensive language, due to limited resources and research in the automatic detection of abusive language mechanisms other than English, this condemnable act is still practiced. This study proposes USAD (Urdu Slang and Abusive words Detection), a lexicon-based intelligent framework to detect abusive and slang words in Perso-Arabic-scripted Urdu Tweets. Furthermore, due to the nonavailability of the standard dataset, we also design and annotate a dataset of abusive, offensive, and slang word Perso-Arabic-scripted Urdu as our second significant contribution for future research. The results show that our proposed USAD model can identify 72.6% correctly as abusive or nonabusive Tweet. Additionally, we have also identified some key factors that can help the researchers improve their abusive language detection models.


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