相关论文: COVID-19 Fake News Detection Using Bidirectional E…

The COVID-19 pandemic has led to a global health crisis, highlighting the need for rapid and accurate virus detection. This research paper examines transfer learning with vision transformers for COVID-19 detection, known for its excellent…

Purpose: We present image classifiers based on Dense Convolutional Networks and transfer learning to classify chest X-ray images according to three labels: COVID-19, pneumonia and normal. Methods: We fine-tuned neural networks pretrained on…

The spread of fake news has caused great harm to society in recent years. So the quick detection of fake news has become an important task. Some current detection methods often model news articles and other related components as a static…

Generated hateful and toxic content by a portion of users in social media is a rising phenomenon that motivated researchers to dedicate substantial efforts to the challenging direction of hateful content identification. We not only need an…

With the rapid growth of online information, the spread of fake news has become a serious social challenge. In this study, we propose a novel detection framework based on Large Language Models (LLMs) to identify and classify fake news by…

With the rise of social media, the spread of fake news has become a significant concern, potentially misleading public perceptions and impacting social stability. Although deep learning methods like CNNs, RNNs, and Transformer-based models…

The novel coronavirus disease (COVID-19) constitutes a public health emergency globally. It is a deadly disease which has infected more than 230 million people worldwide. Therefore, early and unswerving detection of COVID-19 is necessary.…

With the ease of access to information, and its rapid dissemination over the internet (both velocity and volume), it has become challenging to filter out truthful information from fake ones. The research community is now faced with the task…

In the contemporary era, social media platforms amass an extensive volume of social data contributed by their users. In order to promptly grasp the opinions and emotional inclinations of individuals regarding a product or event, it becomes…

The problem associated with the propagation of fake news continues to grow at an alarming scale. This trend has generated much interest from politics to academia and industry alike. We propose a framework that detects and classifies fake…

COVID-19 is one of the most important topic these days, specifically on search engines and news. While fake news are easily shared, scientific papers are reliable sources where information can be extracted. With about 24,000 scientific…

Framing is among the most extensively used concepts in the field of communication science. The availability of digital data offers new possibilities for studying how specific aspects of social reality are made more salient in online…

The significance of efficient and accurate diagnosis amidst the unique challenges posed by the COVID-19 pandemic underscores the urgency for innovative approaches. In response to these challenges, we propose a transfer learning-based…

False news has received attention from both the general public and the scholarly world. Such false information has the ability to affect public perception, giving nefarious groups the chance to influence the results of public events like…

The proliferation of fake news on social media platforms has exerted a substantial influence on society, leading to discernible impacts and deleterious consequences. Conventional deep learning methodologies employing small language models…

In this paper, we explore the use of large language models to assess human interpretations of real world events. To do so, we use a language model trained prior to 2020 to artificially generate news articles concerning COVID-19 given the…

Classification of crisis events, such as natural disasters, terrorist attacks and pandemics, is a crucial task to create early signals and inform relevant parties for spontaneous actions to reduce overall damage. Despite crisis such as…

Transformer-based machine learning models have become an essential tool for many natural language processing (NLP) tasks since the introduction of the method. A common objective of these projects is to classify text data. Classification…

Nowadays, People prefer to follow the latest news on social media, as it is cheap, easily accessible, and quickly disseminated. However, it can spread fake or unreliable, low-quality news that intentionally contains false information. The…

From conspiracy theories to fake cures and fake treatments, COVID-19 has become a hot-bed for the spread of misinformation online. It is more important than ever to identify methods to debunk and correct false information online. In this…