TY - GEN
T1 - A dynamic model on news popularity prediction in online social networks
AU - Wang, Xiaomeng
AU - Fang, Binxing
AU - Zhang, Hongli
AU - Wang, Xing
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/3
Y1 - 2019/3
N2 - With the fast development of smartphone and wireless network, the real-time news spreads faster because people can use mobile client to broese images, video and audio contents. Many people share and comment to express their mends. redicting the popularity of the online content is a hot research poiont and many people concentate on finding out the law of information dissemination. In this paper, taking the Tencent News as a case, we observed that there exists a popularity migration, people somtimes leave comments on irrelevant topics, especially when a hot topic happens. The main contribution of this article is to solve the problem that few or no work for popularity prediction based on topic migration effect. We propose a model based on the reinfoced Poisson process model with the weak tie theory and competitive matrix. Our goal is to accurately estimate the popularity of a given viral topic at final based on the observation of its historical characteristics. Also, this method provides a better performance in the popularity prediction according to an empirical study.
AB - With the fast development of smartphone and wireless network, the real-time news spreads faster because people can use mobile client to broese images, video and audio contents. Many people share and comment to express their mends. redicting the popularity of the online content is a hot research poiont and many people concentate on finding out the law of information dissemination. In this paper, taking the Tencent News as a case, we observed that there exists a popularity migration, people somtimes leave comments on irrelevant topics, especially when a hot topic happens. The main contribution of this article is to solve the problem that few or no work for popularity prediction based on topic migration effect. We propose a model based on the reinfoced Poisson process model with the weak tie theory and competitive matrix. Our goal is to accurately estimate the popularity of a given viral topic at final based on the observation of its historical characteristics. Also, this method provides a better performance in the popularity prediction according to an empirical study.
KW - Big data
KW - Information diffusion
KW - Popularity
KW - Social network
UR - https://www.scopus.com/pages/publications/85067880873
U2 - 10.1109/ITNEC.2019.8729161
DO - 10.1109/ITNEC.2019.8729161
M3 - 会议稿件
AN - SCOPUS:85067880873
T3 - Proceedings of 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2019
SP - 847
EP - 851
BT - Proceedings of 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2019
A2 - Xu, Bing
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2019
Y2 - 15 March 2019 through 17 March 2019
ER -