Sentiment analysis for fake news detection

MA Alonso, D Vilares, C Gómez-Rodríguez, J Vilares - Electronics, 2021 - mdpi.com
In recent years, we have witnessed a rise in fake news, ie, provably false pieces of
information created with the intention of deception. The dissemination of this type of news …

Evaluating deep learning approaches for covid19 fake news detection

A Wani, I Joshi, S Khandve, V Wagh, R Joshi - Combating Online Hostile …, 2021 - Springer
Social media platforms like Facebook, Twitter, and Instagram have enabled connection and
communication on a large scale. It has revolutionized the rate at which information is shared …

Cross-SEAN: A cross-stitch semi-supervised neural attention model for COVID-19 fake news detection

WS Paka, R Bansal, A Kaushik, S Sengupta… - Applied Soft …, 2021 - Elsevier
As the COVID-19 pandemic sweeps across the world, it has been accompanied by a
tsunami of fake news and misinformation on social media. At the time when reliable …

[HTML][HTML] Knowledge graph informed fake news classification via heterogeneous representation ensembles

B Koloski, TS Perdih, M Robnik-Šikonja, S Pollak… - Neurocomputing, 2022 - Elsevier
Increasing amounts of freely available data both in textual and relational form offers
exploration of richer document representations, potentially improving the model …

Transformer based automatic COVID-19 fake news detection system

S Gundapu, R Mamidi - arxiv preprint arxiv:2101.00180, 2021 - arxiv.org
Recent rapid technological advancements in online social networks such as Twitter have led
to a great incline in spreading false information and fake news. Misinformation is especially …

Hc-covid: A hierarchical crowdsource knowledge graph approach to explainable covid-19 misinformation detection

Z Kou, L Shang, Y Zhang, D Wang - Proceedings of the ACM on Human …, 2022 - dl.acm.org
The proliferation of social media has promoted the spread of misinformation that raises
many concerns in our society. This paper focuses on a critical problem of explainable …

A comparative study of machine learning and deep learning techniques for fake news detection

J Alghamdi, Y Lin, S Luo - Information, 2022 - mdpi.com
Efforts have been dedicated by researchers in the field of natural language processing
(NLP) to detecting and combating fake news using an assortment of machine learning (ML) …

Factify 2: A multimodal fake news and satire news dataset

S Suryavardan, S Mishra, P Patwa… - arxiv preprint arxiv …, 2023 - arxiv.org
The internet gives the world an open platform to express their views and share their stories.
While this is very valuable, it makes fake news one of our society's most pressing problems …

g2tmn at constraint@ aaai2021: exploiting CT-BERT and ensembling learning for COVID-19 fake news detection

A Glazkova, M Glazkov, T Trifonov - … on​ Combating On​ line Ho​ st​ ile …, 2021 - Springer
The COVID-19 pandemic has had a huge impact on various areas of human life. Hence, the
coronavirus pandemic and its consequences are being actively discussed on social media …

Arabic Fake News Detection: Comparative Study of Neural Networks and Transformer‐Based Approaches

M Al-Yahya, H Al-Khalifa, H Al-Baity, D AlSaeed… - …, 2021 - Wiley Online Library
Fake news detection (FND) involves predicting the likelihood that a particular news article
(news report, editorial, expose, etc.) is intentionally deceptive. Arabic FND started to receive …