A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Filters
Early detection of rumors based on source tweet-word graph attention networks
2022
PLoS ONE
Preserved Fulltext
Considering the small-world property of social networks, the source tweet-word graph is decomposed from the global graph of rumors, and a rumor detection method based on graph attention network of source ...
tweet-word graph is proposed to fully learn the structure of rumor propagation and the deep representation of text contents. ...
propagation graph, combining textual information or user profiles in rumors for rumor detection. ...
doi:10.1371/journal.pone.0271224
pmid:35816493
pmcid:PMC9273096
fatcat:xxc34zq5bvcivh25vn6qauvyva
Recurrent Graph Neural Networks for Rumor Detection in Online Forums
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
We train the R-GNN on news link categorization and rumor detection, showing superior results to recent baselines. ...
Using Reddit as a case-study, we show how to obtain a derived social graph, and use this graph, Reddit post sequences, and comment trees as inputs to a Recurrent Graph Neural Network (R-GNN) encoder. ...
These platforms have a natural social graph created by users, which provides an inherent graph on which a Graph Neural Network can propagate rumor information. ...
arXiv:2108.03548v1
fatcat:dycxxxjz2nhpjiqx27ir5mijla
Heterogeneous Graph Attention Networks for Early Detection of Rumors on Twitter
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
In this paper, we construct a tweet-word-user heterogeneous graph based on the text contents and the source tweet propagations of rumors. ...
for rumor detection. ...
Subgraph Attention Network Considering that the neighbors of each node in subgraphs have different importance to learn node embedding for rumor detection and inspired by graph attention networks [15] ...
arXiv:2006.05866v1
fatcat:jeuekbvdnfezvilcxhlb7fg3xu
Research status of deep learning methods for rumor detection
2022
Multimedia tools and applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2022 pre-print arXiv:2204.11540v1 fatcat:4oeelrf3gnbmhnr7lgmut2ca4y
Besides, this work summarizes 30 works into 7 rumor detection methods such as propagation trees, adversarial learning, cross-domain methods, multi-task learning, unsupervised and semi-supervised methods ...
, based knowledge graph, and other methods for the first time. ...
has used graph structure adversarial learning for the learning task of propagating graphs, they only consider the detection of abnormal propagation points to help the rumor detection task. ...
doi:10.1007/s11042-022-12800-8
pmid:35469150
pmcid:PMC9022167
fatcat:h5vjukpkyzdhnjhikgtpj347e4
Rumor Detection Based On Propagation Graph Neural Network With Attention Mechanism
2020
Expert systems with applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
On this basis, we propose two models, namely GLO-PGNN (rumor detection model based on the global embedding with propagation graph neural network) and ENS-PGNN (rumor detection model based on the ensemble ...
We first propose a novel way to construct the propagation graph by following the propagation structure (who replies to whom) of posts on Twitter. ...
Acknowledgments The research work is supported by National Natural Science Foundation of China (U1433116) and the Fundamental Research Funds for the Central Universities (NP2017208). ...
doi:10.1016/j.eswa.2020.113595
pmid:32565619
pmcid:PMC7274137
fatcat:pkowkwq5anckfdhc3guh6jer4e
Catch me if you can: A participant-level rumor detection framework via fine-grained user representation learning
2021
Information Processing & Management
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
In this study, we propose a novel participantlevel rumor detection framework. ...
Practically, our results can be used to improve the quality of rumor detection services for social platforms. ...
Acknowledgments This work was supported by National Natural Science Foundation of China (Grant No. 62072077 and No. 61602097), Sichuan Regional Innovation Cooperation Project (Grant No. 2020YFQ0018). ...
doi:10.1016/j.ipm.2021.102678
fatcat:2qvoyb4zkzdihef2bc2zkepny4
Microblog-HAN: A micro-blog rumor detection model based on heterogeneous graph attention network
2022
PLoS ONE
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
However, the existing detection methods fail to take full advantage of the semantics of the microblog information propagation graph. ...
is a graph-based rumor detection model, to capture and aggregate the semantic information using attention layers. ...
This is because the PPC model combines variations from different levels after the propagation path is learned by the RNN and CNN, which is remarkably beneficial to rumor detection. ...
doi:10.1371/journal.pone.0266598
pmid:35413070
pmcid:PMC9004763
fatcat:wcuiz6dqpjhxtijsphw7ngk3ma
Rumor Detection with Self-supervised Learning on Texts and Social Graph
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Rumor detection has become an emerging and active research field in recent years. ...
We term this framework as Self-supervised Rumor Detection (SRD). Extensive experiments on three real-world datasets validate the effectiveness of SRD for automatic rumor detection on social media. ...
Graph Convolutional Network Inspired by the great success of Convolutional Neural Network (CNN), Graph Neural Networks (GNNs) begin to emerge in supervised or semi-supervised tasks like node classification ...
arXiv:2204.08838v1
fatcat:ybmyd4ipxfh3zamwxcd53ha7k4
Modeling microscopic and macroscopic information diffusion for rumor detection
2021
International Journal of Intelligent Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Recently, deep learning solutions have emerged as the de facto methods which detect online rumors in an end-to-end manner. ...
It leverages graph neural networks to learn the macroscopic diffusion of rumor propagation and capture microscopic diffusion patterns using bidirectional recurrent neural networks while taking into account ...
ACKNOWLEDGMENTS This study was supported by National Natural Science Foundation of China (Grant no. 62072077), Sichuan Regional Innovation Cooperation Project (Grant no. 2020YFQ0018), and National Key ...
doi:10.1002/int.22518
fatcat:wfzd5mkynvbqxo32q2kojkh6oq
Attention Based Neural Architecture for Rumor Detection with Author Context Awareness
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
In this research, we propose an ensemble neural architecture to detect rumor on Twitter. ...
whether the shared content is rumor or legitimate news. ...
The topic of rumor detection has gained much interest over the years since it helps prevent problems arising after the rumor has emerged. ...
arXiv:1910.01458v1
fatcat:dsickjmnc5cprogkfw4yrcjtkq
Rumor Detection on Social Media with Graph Structured Adversarial Learning
2020
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
In addition to text information, recent detection methods began to exploit the graph structure in the propagation network. ...
However, without a rigorous design, rumors may evade such graph models using various camouflage strategies by perturbing the structured data. ...
We focus on the attack type that fools the graph neural network-based detection model by manipulating the graph structure. ...
doi:10.24963/ijcai.2020/197
dblp:conf/ijcai/YangLTLLZ20
fatcat:p7tnn3mkkfby3oc4c5dowyplta
Adapting Pre-trained Language Models to Rumor Detection on Twitter
2021
Journal of universal computer science (Online)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
In this paper, we propose an approach that seeks to detect emerging and unseen rumors on Twitter by adapting a pre-trained language model to the task of rumor detection, namely RoBERTa. ...
These circumstances required the development of solutions to monitor and detect rumor in a timely manner. ...
By evaluating their approach on various datasets they have proven the ability of their model to detect unseen emerging rumors. ...
doi:10.3897/jucs.65918
fatcat:bdtfurxsfjastmqsrffdvigafm
Rumor Detection on Social Media: Datasets, Methods and Opportunities
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Many efforts have been taken to detect and debunk rumors on social media by analyzing their content and social context using machine learning techniques. ...
This paper gives an overview of the recent studies in the rumor detection field. ...
Liu and Wu (2018) construct user representations using network embedding approaches on the social network graph. ...
arXiv:1911.07199v1
fatcat:h4fk3dyodjgyvffwuo6q5d2tnm
GCNRDM: A Social Network Rumor Detection Method Based on Graph Convolutional Network in Mobile Computing
2021
Wireless Communications and Mobile Computing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
The innovation of the paper proposes a rumor detection model based on the graph convolutional network, which lies in considering the propagation structure among users. It has a strong practical value. ...
We use a high-order graph neural network (K-GNN) to extract the rumor posting features. ...
[14] constructed a rumor propagation tree kernel to detect rumors by evaluating the similarity between rumor propagation tree structures. ...
doi:10.1155/2021/1690669
fatcat:yu4ks7t2xzftfedwcwiveomgmu
The Future of Misinformation Detection: New Perspectives and Trends
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
We first give a brief review of the literature history of MID, based on which we present several new research challenges and techniques of it, including early detection, detection by multimodal data fusion ...
, and explanatory detection. ...
[114] also explore whether the detection of emerging rumors could be benefited by the knowledge acquired from historical crowdsourced data. ey observe that similar rumors o en lead to similar behavior ...
arXiv:1909.03654v1
fatcat:34h2os2pzrbm3kqluk5uajtr6i
« Previous
Showing results 1 — 15 out of 771 results