Analyzing topics in social media for improving digital twinning based product development

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外文摘要：Digital twinning enables manufacturers to create digital representations of physical entities,thus implementing virtual simulations for product development.Previous efforts of digital twinning neglect the decisive consumer feedback in product development stages,failing to cover the gap between physical and digital spaces.This work mines real-world consumer feedbacks through social media topics,which is significant to product development.We specifically analyze the prevalent time of a product topic,giving an insight into both consumer attention and the widely-discussed time of a product.The primary body of current studies regards the prevalent time prediction as an accompanying task or assumes the existence of a preset distribution.Therefore,these proposed solutions are either biased in focused objectives and underlying patterns or weak in the capability of generalization towards diverse topics.To this end,this work combines deep learning and survival analysis to predict the prevalent time of topics.We propose a specialized deep survival model which consists of two modules.The first module enriches input covariates by incorporating latent features of the time-varying text,and the second module fully captures the temporal pattern of a rumor by a recurrent network structure.Moreover,a specific loss function different from regular survival models is proposed to achieve a more reasonable prediction.Extensive experiments on real-world datasets demonstrate that our model significantly outperforms the state-of-the-art methods.

外文关键词：

Digital twinningProduct developmentTopic analysisSocial media

作者：

Wenyi Tang、Ling Tian、Xu Zheng、Ke Yan

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作者单位：

School of Computer Science and Engineering,University of Electronic Science and Technology of China,Chengdu,611731,China

基金：

Sichuan Science and Technology ProgramSichuan Science and Technology ProgramSichuan Science and Technology ProgramNational Natural Science Foundation of China(NSFC)Young Scientists Fund of the National Natural Science Foundation of ChinaFundamental Research Funds for the Central Universities

项目编号：

2019YFG05072020YFG03282021YFG0018U19A205961802050ZYGX2021J019

出版年：

2024

DOI：

10.1016/j.dcan.2022.04.016

数字通信与网络(英文)

ISSN：

年,卷(期)：2024.10(2)

参考文献量40