@inproceedings{7e0a1a7be7644c60beaf2bf3e107ec2e,
title = "Analyzing and predicting the popularity of online content using the weak ties theory",
abstract = "With the rapid development of online social networks (OSNs), a huge amount of user generated online content is gradually affecting people's lives. Popularity prediction of online content aims to predict the popularity in the future based on its early diffusion status. Existing models for popularity prediction are mostly based on discovering network features or fitting the equation into a varying time function which seldom make full use of the law of sociology. The main contribution of this article is to solve the problem that the accuracy of current popularity prediction model is not high enough and few or no work based on sociology. In this paper, we find that there exists a high linear correlation between the proportion of faithful fans in Facebook homepage with frequent shares in the early and the future popularity. The statistical results about Facebook remind us that the weak ties theory plays an important role in prediction task. Furthermore, an experimental study clearly illustrates that the effectiveness of the proposed method.",
keywords = "Information diffusion, Popularity, Social networks, Weak ties theory",
author = "Xiaomeng Wang and Binxing Fang and Hongli Zhang and Xing Wang",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019 ; Conference date: 10-08-2019 Through 12-08-2019",
year = "2019",
month = aug,
doi = "10.1109/HPCC/SmartCity/DSS.2019.00239",
language = "英语",
series = "Proceedings - 21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1743--1748",
editor = "Zheng Xiao and Yang, \{Laurence T.\} and Pavan Balaji and Tao Li and Keqin Li and Albert Zomaya",
booktitle = "Proceedings - 21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019",
address = "美国",
}