Department of Computer Science and Engineering

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Browsing Department of Computer Science and Engineering by Author "Kumar, Sudhanshu"

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    Fake News Detection of Hindi News Dataset using various Machine Learning Based Approaches
    (Department of Computer Science & Engineering, NITS, 2022) Kumar, Sudhanshu
    Fake news has been in existence even before the rise of the printing press. But, the rise in the number of fake news has been exponential in the age of social media and the internet. It has become very easy for anyone to post, comment, or share whatever he/she wants with the help of a device and the internet. Detecting fake news is difficult because the content is made to look so reliable that it seems to be coming from a reliable source. Although the problem of fake news is existing for centuries, it is become more dangerous because of the internet and social media. Mostly false information is spread through social media despite lots of investment are done by the social media companies to find fake news and remove them. Although lots of research have been done in this field of fake news, very less work has been reported for the Hindi language. As such, most of the research work is biased about the news of a particular domain (i.e. politics) which may cause in dataset bias. For our work, a Hindi news dataset is created. For feature extraction, Word2Vec and tf-idf have been used. For the classification task, 2 traditional machine learning approaches, i.e. Naive Bayes and Logistic regression, 1 deep learning approach i.e. LSTM and 2 advanced pre-trained approach are used based on BERT and RoBERTa. Based on overall accuracy all over the datasets, logistic regression outperforms the Naive Bayes model evaluated using a conventional ML approach. The efficiency of the LSTM model is 94.45 percent. BERT, out of the two pre-trained sophisticated NLP models we worked on (i.e., BERT and RoBERTa), has the best result of 98.13 percent.