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@article{155732,
        author = {Nithin Kumar P and Narasimha M and P Neeraj Aravindhakshan and Sai Sanjan Reddy and Dr. Anitha K},
        title = {Genetic Programming Approach to Detect Hate Speech in Social Media},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {1},
        pages = {1547-1552},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=155732},
        abstract = {Now-a-days, social media has become part of our day to day lives. More than half of the world makes use of social media. With the increased use of social media, there have been many problems that are rising. Hate speech is one among them. Since there are billions of users using social media, it has become a big problem to deal with as it can be identified based on user’s report to such action. It’s difficult to monitor and detect the hate speech and on social media platforms. There is a need for detecting and avoiding the hate speech from circulating in social media. The language used and the size of the content pose problem for the traditional machine learning algorithms. Therefore, the genetic programming approach along with ml algorithm is used to detect hate speech because of the better performance it offers.},
        keywords = {Voting classifier, English Twitter dataset, Universal Sentence Encoder, GP.},
        month = {},
        }