• Title of article

    Humor Detection in Persian: A Transformers-Based Approach

  • Author/Authors

    Najafi-Lapavandani ، Fateme Faculty of Mathematics Computer Science - Amirkabir University of Technology , Shirali-Shahreza ، Mohammad Hasan Faculty of Mathematics Computer Science - Amirkabir University of Technology

  • From page
    56
  • To page
    62
  • Abstract
    Humor is a linguistic device that can make people laugh, and in the case of expressing opinions, it can transform a phrase’s polarity. Humorous sentences presenting ideas and criticism, occasionally using informal forms, have made their way to social media platforms like Twitter in almost every domain. Persian speakers likewise express their opinions through humorous tweets on Twitter. As one of the early efforts for detecting humor in Persian, the current research proposes a model by fine-tuning a transformer-based language model on a Persian humor detection dataset. The proposed model has an accuracy of 84.7% on the test set. Moreover, This research introduced a dataset of 14,946 automatically-labeled tweets for humor detection in Persian.
  • Keywords
    Humor Detection , Sentiment Analysis , Natural Language Processing , Deep learning , Persian language
  • Journal title
    International Journal of Information and Communication Technology Research
  • Journal title
    International Journal of Information and Communication Technology Research
  • Record number

    2767226