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fake-news-detection
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Fake News Spreading Mitigation Via Tracing Information In Social Networks
, M.Sc. Thesis Sharif University of Technology ; Rabiee, Hamid Reza (Supervisor)
Abstract
Expansion of using social networks for reading and sharing news on the one hand, allows for quick and easy access to the news, but on the other hand, increases the spread of fake news and misleads many users. Therefore, identifying the fake news and attempting to mitigate its spreading on social networks is one of the major research areas in recent years. An important issue in this regard is reducing the time gap between news release time and identifying it as fake and starting to take action. Many researches has been done on detection of fake news, but since there is a trade-off between minimizing the time gap and maximizing accuracy, work on these models continues. There are also different...
Online Detection Of Multi-Modal Fake News
, M.Sc. Thesis Sharif University of Technology ; Rabiee, Hamid Reza (Supervisor) ; Fazli, Mohammad Amin (Supervisor)
Abstract
Today, social networks have provided an environment for disseminating all kinds of information and news among the people. One of the challenges of ex-panding social networks is reading and trusting fake news propagating against accurate information. Fake news is false information that the author intention-ally produces and publishes. Due to the destructive effects of spreading fake news, determining the trustworthiness of news is one of the critical issues in the so-cial, political, and economic fields. In this research, we worked on detecting fake news on social media using multimodal data. To solve the problem of fake news detection, we used the text and images of the information. Transfer...
Exploring the impact of machine translation on fake news detection: A case study on Persian tweets about COVID-19
, Article 29th Iranian Conference on Electrical Engineering, ICEE 2021, 18 May 2021 through 20 May 2021 ; 2021 , Pages 540-544 ; 9781665433655 (ISBN) ; Ebrahimi, S. F ; Bahrani, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2021
Abstract
Fake news detection has become an emerging and critical topic of research in recent years. One of the major complications of fake news detection lies in the fact that news in social networks is multilingual, and therefore developing methods for each and every language in the world is impossible, especially for low resource languages like Persian. In an effort to solve this problem, researchers use machine translation to uniform the data and develop a method for the uniformed data. In this paper, we aim to explore the impacts of machine translation on fake news detection. For this purpose, we extracted and labeled a dataset of Persian Tweets from Twitter on the subject of COVID-19 and...