Faculty Publications

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    Fake News Detection in Hindi Using Embedding Techniques
    (Institute of Electrical and Electronics Engineers Inc., 2022) Shailendra, P.; Rashmi, M.; Ramu, S.; Guddeti, R.M.R.
    Internet users have been rapidly increasing in recent years, especially in India. That is why nearly everything operates in an online mode. Sharing information has also become simple and easy due to the internet and social media. Almost everyone now shares news in the community without even considering the source of information. As a result, there is the issue of disseminating false, misleading, or fabricated data. Detecting fake news is a challenging task because it is presented in such a form that it looks like authentic information. This problem becomes more challenging when it comes to local languages. This paper discusses several deep learning models that utilize LSTM, BiLSTM, CNN+LSTM, and CNN+BiLSTM. On the Hostility detection dataset in Hindi, these models use Word2Vec, IndicNLP fastText, and Facebook's fastText embeddings for fake news detection. The proposed CNN+BiLSTM model with Facebook's fastText embedding achieved an F1-score of 75%, outperforming the baseline model. Additionally, the BiLSTM using Facebook's fastText outperforms CNN+BiLSTM using Facebook's fastText on the F1-score. © 2022 IEEE.
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    Fake News Detection for Hindi Language
    (CEUR-WS, 2022) Madathil, K.T.; Mirji, N.; Charan, R.; Anand Kumar, A.M.
    The understanding of the term “Fake news†varies from one individual to the other. If we look into the basic meaning of “Fake news†, it refers to inappropriate and made up news. In most cases, the news is made up of baseless sources and facts. These news generally mislead the reader and are generally published for one’s own benefit or to defame others. In recent years, a large population is active on various social media platforms and hence they have become the major medium through which fake news is circulated. A lot of fake news is been circulated in local languages as well. Also most of the existing work is based on the English language and only very little work is done using resource scare language for fake news identification like Indic Languages. So this paper focuses to define false news and suggest an effective method for detecting fake news in Hindi using standard machine learning algorithms like Multi-layer Perceptron and Naive Bayes and deep learning techniques like transforms - mainly mBERT. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).