Deep Spatial-Temporal Structure Learning for Rumor Detection on Twitter, Neural Computing and Applications, 2020
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Updated
Aug 23, 2020 - Python
Deep Spatial-Temporal Structure Learning for Rumor Detection on Twitter, Neural Computing and Applications, 2020
This is REPORT model for rumor detection
Data and Demo for ARGH!
This repository contains AI models that identify deceptive content and combat misinformation
The 14th National College Student Information Security Competition Entry: "Sina Weibo Rumor Detection System"
This repository stores the implementation of trigger identification task on Shanghai-HK Interdisciplinary Shared Tasks (2022).
Original PyTorch Implementation for the EMNLP 2023 Paper "Beyond Detection: A Defend-and-Summarize Strategy for Robust and Interpretable Rumor Analysis on Social Media"
Source Code for TrustCom2022 Accepted Paper " 'Comments Matter and The More The Better': Improving Rumor Detecion with User Comments".
Source code for the publication "Deep Feature Fusion for Rumor Detection on Twitter"
Paper list of misinformation research using (multi-modal) large language models, i.e., (M)LLMs.
Building model in order to identify whether a tweet is rumor
English and Turkish Misinformation Detection Dataset from "MiDe22: An Annotated Multi-Event Tweet Dataset for Misinformation Detection"
Detect rumors on Weibo by PyTorch.
Codes and Datasets for our WSDM 2022 Paper: "MTLTS: A Multi-Task Framework To Obtain Trustworthy Summaries From Crisis-Related Microblogs"
PyTorch implementation for the FinerFact model in the AAAI 2022 paper Towards Fine-Grained Reasoning for Fake News Detection
The public code for paper A Graph Convolutional Encoder and Decoder Model for Rumor Detection which is accepted by DSAA 2020
Deep Structure Learning for Rumor Detection on Twitter (IJCNN 2019)
This repository contains code for the paper "RP-DNN: A Tweet level propagation context based deep neural networks for early rumor detection in Social Media" By J. Gao, S. Han, X. Song, et al. - LREC 2020
This repo is a collection of AWESOME things about fake news detection, including papers, code, etc.
Links to conference/journal publications in automated fact-checking (resources for the TACL22/EMNLP23 paper).
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