@inproceedings{7405c39e227844aea7dd4327b9186847,
title = "Predicting the popularity of online content based on the weak ties theory",
abstract = "With the rapid development of network. The multimedia information spreads faster since the rise of social network where people can create and share images, video and audio contents. Online content captures online behavior of users who communicate or interact on a diversity of issues and topics. How to predict the popularity of the online content happened recently is a hot topic and lots of researchers are trying to find out the law of information diffusion hidden in it. However, many models missed to make full use of the principles of social science. The main contribution of this article is to solve the problem that there are few popularity prediction work based on principles of sociology. We propose a model based on weak tie theory with a linear regression approach on Facebook. 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.",
keywords = "Diffusion, Popularity, Social network, Strong ties",
author = "Xiaomeng Wang and Binxing Fang and Hongli Zhang and Shen Su",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 3rd IEEE International Conference on Data Science in Cyberspace, DSC 2018 ; Conference date: 18-06-2018 Through 21-06-2018",
year = "2018",
month = jul,
day = "16",
doi = "10.1109/DSC.2018.00062",
language = "英语",
series = "Proceedings - 2018 IEEE 3rd International Conference on Data Science in Cyberspace, DSC 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "386--391",
booktitle = "Proceedings - 2018 IEEE 3rd International Conference on Data Science in Cyberspace, DSC 2018",
address = "美国",
}