0% Complete
Home
/
11th International Conference on Computer and Knowledge Engineering
A Novel Method For Fake News Detection Based on Propagation Tree
Authors :
Mansour Davoudi
1
Mohammad Reza Moosavi
2
Mohammad Hadi Sadreddini
3
1- Department of Computer Science and Engineering and IT, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.
2- Department of Computer Science and Engineering and IT, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.
3- Department of Computer Science and Engineering and IT, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.
Keywords :
Fake news detection, Social media, LSTM network, Propagation tree
Abstract :
Nowadays, online social media play a significant role in news broadcast due to their convenience, speed, and accessibility. Social media platforms leverage the rapid production of a large volume of information and cause the propagation of untrustworthy and fake news. Since fake news is engineered to persuade a wide range of readers intentionally, it is difficult to detect them just based on the news content, and more information, such as the social context, is needed. In this paper, we propose a new model based on analyzing the propagation tree for detecting fake news. We dynamically extract novel features from the constructed propagation trees over time. To predict the veracity of a news article, a kind of recurrent neural network (LSTM) is used to capture the temporal dynamics of extracted features and identify the evolution pattern of the propagation tree over time. Our proposed model is evaluated on the FakeNewsNet repository, which consists of two recent well-known datasets in the field, namely PolitiFact and GossipCop. Our results show encouraging performance, outperforming the state-of-the-art methods by 2.3% on the PolitiFact and 1.2% on the GossipCop datasets
Papers List
List of archived papers
City Intersection Clustering and Analysis Based on Traffic Time Series
Mohammad Aminazadeh - Fakhroddin Noorbehbahani
A novel hybrid DMHS-GMDH algorithm to predict COVID-19 pandemic time series
Ahmad Taheri - Shahriar Ghashghaei - Amin Beheshti - Keyvan RahimiZadeh
Diagnosis of Depression Based on New Features Extractive from the Frequency Space of the EEG
Melika Changizi - Saeid Rashidi
Overview of Electric Vehicles Charging Stations in Smart Grids
Mohammed Wadi - Wisam Elmasry - Mohammed Jouda - Hossein Shahinzadeh - Gevork B. Gharehpetian
FaaScaler: An Automatic Vertical and Horizontal Scaler for Serverless Computing Environments
Zahra Rezaei - Saeid Abrishami - Seid Nima Moeintaghavi
LPCNet: Lane detection by lane points correction network in challenging environments based on deep learning
Sina BaniasadAzad - Seyed Mohammadreza Mousavi mirkolaei
Automated Person Identification from Hand Images\\using Hierarchical Vision Transformer Network
Zahra Ebrahimian - Seyed Ali Mirsharji - Ramin Toosi - Mohammad Ali Akhaee
DPRNN-FORMER: AN EFFICIENT WAY TO DEAL WITH BLIND SOURCE SEPARATION
Ramin Ghorbani - Sajad Haghzad Klidbary
Evolutionary Approach to GAN Hyperparameter Tuning: Minimizing Discriminator and Generator Loss Functions
Sajad Haghzad Klidbary - Anahita Babaei - Ramin Ghorbani
Effect of Tissue Excitation in Breast Cancer Detection from Ultrasound RF Time Series: Phantom studies
Elaheh Norouzi Ghehi - Ali Fallah - Saeid Rashidi - Maryam Mehdizadeh Dastjerdi
more
Samin Hamayesh - Version 41.3.1