Results 1 to 10 of about 98,441 (260)

Exploring Spillover Effects for COVID-19 Cascade Prediction [PDF]

Entropy, 2022
An information outbreak occurs on social media along with the COVID-19 pandemic and leads to an infodemic. Predicting the popularity of online content, known as cascade prediction, allows for not only catching in advance information that deserves ...
Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang   +3 more
doaj   +2 more sources

Information Cascades Prediction With Graph Attention

Frontiers in Physics, 2021
The cascades prediction aims to predict the possible information diffusion path in the future based on cascades of the social network. Recently, the existing researches based on deep learning have achieved remarkable results, which indicates the great ...
Zhihao Chen, Zhihao Chen, Zhihao Chen, Jingjing Wei, Shaobin Liang, Shaobin Liang, Shaobin Liang, Tiecheng Cai, Tiecheng Cai, Tiecheng Cai, Xiangwen Liao, Xiangwen Liao, Xiangwen Liao, Xiangwen Liao   +13 more
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Structural-topic aware deep neural networks for information cascade prediction [PDF]

PeerJ Computer Science
It is critical to accurately predict the future popularity of information cascades for many related applications, such as online opinion warning or academic influence evaluation. Despite many efforts devoted to developing effective prediction approaches,
Bangzhu Zhou, Xiaodong Feng, Hemin Feng
doaj   +3 more sources

A cascade information diffusion prediction model integrating topic features and cross-attention

Journal of King Saud University: Computer and Information Sciences, 2023
Information cascade prediction is a crucial task in social network analysis. However, previous research has only focused on the impact of social relationships on cascade information diffusion, while ignoring the differences caused by the characteristics ...
Xiaoyang Liu, Haotian Wang, Asgarali Bouyer   +2 more
doaj   +3 more sources

Popularity Prediction of Online Contents via Cascade Graph and Temporal Information

Axioms, 2021
Predicting the popularity of online content is an important task for content recommendation, social influence prediction and so on. Recent deep learning models generally utilize graph neural networks to model the complex relationship between information ...
Yingdan Shang, Bin Zhou, Ye Wang, Aiping Li, Kai Chen, Yichen Song, Changjian Lin   +6 more
doaj   +3 more sources

Landslide Susceptibility Prediction Modeling Based on Remote Sensing and a Novel Deep Learning Algorithm of a Cascade-Parallel Recurrent Neural Network

Sensors, 2020
Landslide susceptibility prediction (LSP) modeling is an important and challenging problem. Landslide features are generally uncorrelated or nonlinearly correlated, resulting in limited LSP performance when leveraging conventional machine learning models.
Li Zhu, Lianghao Huang, Linyu Fan, Jinsong Huang, Faming Huang, Jiawu Chen, Zihe Zhang, Yuhao Wang   +7 more
doaj   +3 more sources

Fusing temporal and structural information via subgraph sampling and multi-head attention for information cascade prediction [PDF]

Scientific Reports
The rapid expansion of online social networks has led to explosive growth of information cascades, necessitating effective prediction methods for both research and industry.
Jie Wang, Jinze Li, Chun Liu, Yan Peng, Xiao Li   +4 more
doaj   +2 more sources

From chaos to care: Personalized AI for early cardiac arrhythmia warning [PDF]

Machine Learning with Applications
Cardiac arrhythmias are abnormal heart rhythms arising from disordered electrical dynamics that contribute significantly to global morbidity and mortality.
Suvankar Halder, Christopher M. Kim, Vipul Periwal   +2 more
doaj   +2 more sources

Predicting the Popularity of Information on Social Platforms without Underlying Network Structure

Entropy, 2023
The ability to predict the size of information cascades in online social networks is crucial for various applications, including decision-making and viral marketing.
Leilei Wu, Lingling Yi, Xiao-Long Ren, Linyuan Lü   +3 more
doaj   +1 more source

Why cannot long-term cascade be predicted? Exploring temporal dynamics in information diffusion processes

Royal Society Open Science, 2021
Predicting information cascade plays a crucial role in various applications such as advertising campaigns, emergency management and infodemic controlling. However, predicting the scale of an information cascade in the long-term could be difficult.
Ren-Meng Cao, Xiao Fan Liu, Xiao-Ke Xu
doaj   +1 more source