NNMLInf:Social Influence Prediction with Neural Network Multi-label Classification

摘要：

　　Social platforms such as Weibo,Facebook and Twitter have become a part of daily life,where people can exchange information.In this process,people's behaviors often influence each other.Social influ-ence prediction has become one of the hot issues at present.In this paper,NNMLInf social influence prediction model is constructed based on neural network multi-label classification.People's net-work structure features are taken as the network input,and their behaviors are divided into multiple labels as the network output.Node2vec is adopted to extract network representative features of users.This model combines the network structure with human behaviors,and the prediction results can be more practical.The experiment carried on BlogCatalog,Flickr and Youtube shows that NNMLInf model performs better than traditional approaches such as DT(decision tree),SVM(support vector machine),and better expresses social influence.

关键词： Social Influence Neural Network Multi-label Classification Social Network

作者: Xupeng Wang Zhongwen Guo Xi Wang Shiyong Liu Wei Jing Yuan Liu

作者单位: Department of Computer Science and Technology,Ocean University of China Qingdao,Shandong,China

会议类型: 国际会议

会议名称: 2019国图灵大会(ACM Turing Celebration conference-China 2019 )

会议地点: 成都

会议语种:英文

页码: 261-265

在线出版日期: 2019-05-17（万方平台首次上网日期，不代表论文的发表时间）