Journal
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
Volume 7, Issue 1, Pages 24-34Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCSS.2019.2950139
Keywords
Diffusion inferring; information propagation; open social network (OSN); recommender system
Funding
- Japan Society for the Promotion of Science (JSPS) KAKENHI [JP16K00117, JP19K20250]
- KDDI Foundation
- National Key Research and Development Program of China [2016YFB0801003]
- National Natural Science Foundation of China [61562004, 61431008]
- Leading Initiative for Excellent Young Researchers, MEXT, Japan
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Open social network (OSN) plays a more significant role in information propagation through the rapid developing of information technology. Since information diffusion is an essential process happens in OSN, it has been studied in many studies. Several models have been proposed to infer the diffusion process and reproduce diffusion network. However, these methods have two critical problems: 1) ignoring the effects of user social characteristics and 2) inaccuracy resulted from calculating the influence of different features independently. To address these limitations, a diffusion inferring method based on a recommender system (DIM-SPTF) was proposed. The DIM-SPTF method considers the propagation process between the users as the recommendation process of information and employs a recommender system to infer the propagation relationship. Through determining the propagation relations among all users in the observed topic data set, an information diffusion network can be finally obtained. Experimental results show that DIM-SPTF leads to improvements in performance compared with the state-of-the-art methods.
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