We can obtain these features from forums, social environments and even from part of accompanying images, so we review the present work in the succeeding three areas: fake news detection based on traditional machine learning, fake news detection based on single modal data, and fake news detection...
Fake News detection, https://www.kaggle.com/jruvika/fake-news-detection, last accessed 2019/07/13. Google Scholar Cited by (158) Detection of fake news using deep learning CNN–RNN based methods 2022, ICT Express Citation Excerpt : They use Fake News Dataset [16], and as a result, thei...
https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset https://huggingface.co/bert-base-uncased https://keras.io/api/keras_nlp/tokenizers/tokenizer/ https://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.TfidfVectorizer.html ...
the work presented by Jwa et al.30had used it to a significant effect. The proposed model, exBAKE, applied BERT for the first time in fake news detection using a headline-body dataset. BERT was pre-trained with additional data explicitly related to the news to better express...
Recent state-of-the-art of fake news detection: A review 2020 International Conference for Emerging Technology (INCET), IEEE (2020), pp. 1-6 CrossrefGoogle Scholar [8] Zhou X., Zafarani R. A survey of fake news: Fundamental theories, detection methods, and opportunities ACM Comput. Surv...
Trust and Believe 50,000 users Manually annotated, Active learning Influence score Active learning approach Twitter Small dataset 5. Discussion and challenges Solving the problem of fake news detection and minimizing their impact on society is one of the important issues being considered in the researc...
Various researchers have recently addressed the problem of fake review detection. The most common approach is to use machine learning (ML) methods to build a binary classifier, working in a carefully designed feature space. However, to make an ML model, there needs to be a dataset that it ca...
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