Title :
Neural Network Based Attention Degree Prediction for Internet Incidents in One-Crest Period
Author :
He, Sha ; Wang, Yuzi ; Wang, Yue ; Zhang, Qingjie ; Zhang, Yuejin ; Wang, Tianmei
Author_Institution :
Sch. of Inf., Central Univ. of Finance & Econ., Beijing, China
Abstract :
Observing an Internet incident, we find that its attention degrees develop in multiple wave crests. We propose a basic model to predict the trend of one wave crest based on back propagation (BP) neural network. Simulation experiments show that our model can predict one-crest trend of an Internet incident under the assumption that its maximum attention degree can be estimated. Our work can serve as an auxiliary tool for social or commercial workers to make decisions based on public opinions.
Keywords :
Internet; backpropagation; decision making; neural nets; BP neural network; Internet incidents; back propagation neural network; commercial workers; decision making; maximum attention degree; multiple wave crests; neural network based attention degree prediction; one-crest period; public opinions; social workers; Biological neural networks; Educational institutions; Internet; Market research; Predictive models; Training; BP neural network; Internet incidents; attention degree; forcasting; public opinions;
Conference_Titel :
Management of e-Commerce and e-Government (ICMeCG), 2012 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-2943-9
DOI :
10.1109/ICMeCG.2012.46
