IDEAS home Printed from https://ideas.repec.org/a/hin/complx/6684995.html
   My bibliography  Save this article

USAD: An Intelligent System for Slang and Abusive Text Detection in PERSO-Arabic-Scripted Urdu

Author

Listed:
  • Nauman Ul Haq
  • Mohib Ullah
  • Rafiullah Khan
  • Arshad Ahmad
  • Ahmad Almogren
  • Bashir Hayat
  • Bushra Shafi

Abstract

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.

Suggested Citation

  • Nauman Ul Haq & Mohib Ullah & Rafiullah Khan & Arshad Ahmad & Ahmad Almogren & Bashir Hayat & Bushra Shafi, 2020. "USAD: An Intelligent System for Slang and Abusive Text Detection in PERSO-Arabic-Scripted Urdu," Complexity, Hindawi, vol. 2020, pages 1-7, November.
    • Handle: RePEc:hin:complx:6684995
    DOI: 10.1155/2020/6684995
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2020/6684995.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2020/6684995.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2020/6684995?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:complx:6684995. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.