International Conference on Computer and Knowledge Engineering

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Hate Sentiment Recognition System For Persian Language

Authors :

Pegah Shams jey¹ Arash Hemmati² Ramin Toosi³ Mohammad ali Akhaee⁴

1- School of Electrical and Computer Engineering, K. N. Toosi University of Technology 2- School of Electrical and Computer Engineering, College of Engineering, University of Tehran 3- School of Electrical and Computer Engineering, College of Engineering, University of Tehran 4- School of Electrical and Computer Engineering, College of Engineering, University of Tehran

Keywords :

hate speech

Abstract :

People’s lives in societies, today are tied to social networks and these networks face problems such as the existence of hateful speech. Most social networks try to identify and prevent the spread of this phenomenon by using natural language processing (NLP) methods. On the internet, hate speech causes arguments between different groups in society. Given that anyone is able to put any content on social media in the form of a short text, this leads to the uncontrollable spread of hatred on social networks and can cause harm to individuals and various groups in society. This is necessary to have control over users’ content on social media. In this study a method for identifying hateful content in short texts is proposed. First, TF-IDF of word-based and character-based n-grams are calculated. Then, employing calibrated support vector machine (SVM), the probability of each n-grams related to hatred is calculated. Finally, another SVM is applied for final classification. The proposed method is compared to the state-of-the-art methods using In- stagram comments on various performance metrics. Results show that the proposed method outperforms the previous studies.

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