A Novel Embedding Method for News Diffusion Prediction
Liu,Ruoran1,2; Li,Qiudan1; Wang,Can1,2; Wang,Lei1; Zeng,Daniel Dajun1,2,3
Conference NameAAAI Conference on Artificial Intelligence
Conference Date2018-2
Conference PlaceNew Orleans, Louisiana, USA

News diffusion prediction aims to predict a sequence of news sites which will quote a particular piece of news. Most of previous propagation models make efforts to estimate propagation probabilities along observed links and ignore the characteristics of news diffusion processes, and they fail to capture the implicit relationships between news sites. In this paper, we propose an algorithm to model the news diffusion processes in a continuous space and take the attributes of news into account. Experiments performed on a real-world news dataset show that our model can take advantage of news' attributes and predict news diffusion accurately.

Indexed ByEI
Document Type会议论文
Affiliation1.Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences
3.University of Arizona
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Liu,Ruoran,Li,Qiudan,Wang,Can,et al. A Novel Embedding Method for News Diffusion Prediction[C],2018.
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