电子学报2017，Vol.45Issue(12)：2987-2996,10.DOI:10.3969/j.issn.0372-2112.2017.12.022
基于能量优化的微博用户转发行为预测
Predicting Microblog User Retweet Behaviors Based on Energy Optimization
摘要
Abstract
Predicting user retweet behaviors is the basis of building the information diffusion model in micorblog social networks,and also is applied for a variety of fields such as public opinion monitoring,viral marketing,political campaign etc.In order to improve the accuracy of predicting user retweet behaviors,under the MRF (Markov Random Field) framework,the paper comprehensively analyzes the effects caused by user attributes,microblog contents,the constraints between user retweet behaviors and the group retweet priors,and constructs the corresponding energy function based on the logistic regression model to globally predict user retweet behaviors.Experimental results show user retweet behaviors not only depend on user attributes,and micorblog contents,but also are influenced by the constraints between user retweet behaviors and the group retweet priors in varying degrees.Compared to the traditional methods,our proposed method can accurately model user retweet behaviors and thus achieve satisfactory results.关键词
新浪微博/转发预测/能量优化/逻辑回归Key words
sina microblog/retweet predicting/energy optimization/logistic regression分类
信息技术与安全科学引用本文复制引用
王伟,张效尉,任国恒,秦东霞,刘琳琳..基于能量优化的微博用户转发行为预测[J].电子学报,2017,45(12):2987-2996,10.基金项目
国家自然科学基金(No.U1404620,No.U1404622) （No.U1404620,No.U1404622）
河南省自然科学基金(No.162300410347) （No.162300410347）
河南省科技攻关项目(No.172102310727,No.162102310589,No.162102210396,No.162102310590) （No.172102310727,No.162102310589,No.162102210396,No.162102310590）
河南省高校重点科研项目(No.17A520018,No.17A520019,No.15A520116,No.16B520034,No.16A520105) （No.17A520018,No.17A520019,No.15A520116,No.16B520034,No.16A520105）
周口师范学院高层次人才科研启动基金(No.zknuc2015103) （No.zknuc2015103）
