Human mobility in interest space and interactive random walk

Journal article

Compared with the well-studied topic of human mobility in real geographic space, only a few studies focus on human mobility in virtual space, such as interests, knowledge, ideas, and so on. However, it relates to the issues like public opinion management, knowledge diffusion, and innovation. In this paper, we assume that the interests of a group of online users can span an Euclidean space which is called interest space, and the transfers of user interests can be modelled as Lévy Flight in the interest space. Considering the interaction between users, we assume that the random walkers are not independent but interacting with each other indirectly via the digital resources in the interest space. The proposed model in this paper successfully reproduced a set of scaling laws for describing the growth of attention flow networks of online communities, and obtaining similar ranges of users’ scaling exponents with empirical data. Further, we inferred parameters for describing the individual behaviours of the users according to the scaling laws of empirical attention flow network. Our model can not only provide theoretical understanding of human online behaviours but also has broad potential applications such as dissemination and public opinion management, online recommendation, etc.

Authors: Zeng, F; Gong, L; Liu, J; Zhang, J; Chen, Q

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: IOP Publishing
• Journal: Journal of Physics: Complexity
• Volume: 1
• Issue: 2
• Pages: 025004-025004
• Publication date: 2020-07-03
• DOI: 10.1088/2632-072X/ab7f4f
• EISSN: 2632-072X
• ISSN: 2632-072X
• Language: English
• Keywords: Scaling; Public opinion; Statistics; Law; Data science; Euclidean space; Empirical research; Set (abstract data type); Space (punctuation); Point of interest; Artificial intelligence; Diffusion; Machine learning; Focus (optics); Multidimensional scaling; Computer science; Mathematics; Random walk; Theoretical computer science