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Efficiency of Algorithms for Computing Influence and Information Spreading on Social Networks
Content Provider | MDPI |
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Author | Matias, Ijäs Kuikka, Vesa Aalto, Henrik Kaski, Kimmo K. |
Copyright Year | 2022 |
Description | Modelling interactions on complex networks needs efficient algorithms for describing processes on a detailed level in the network structure. This kind of modelling enables more realistic applications of spreading processes, network metrics, and analyses of communities. However, different real-world processes may impose requirements for implementations and their efficiency. We discuss different transmission and spreading processes and their interrelations. Two pseudo-algorithms are presented, one for the complex contagion spreading mechanism using non-self-avoiding paths in the modelling, and one for simple contagion processes using self-avoiding paths in the modelling. The first algorithm is an efficient implementation that can be used for describing social interaction in a social network structure. The second algorithm is a less efficient implementation for describing specific forms of information transmission and epidemic spreading. |
Starting Page | 262 |
e-ISSN | 19994893 |
DOI | 10.3390/a15080262 |
Journal | Algorithms |
Issue Number | 8 |
Volume Number | 15 |
Language | English |
Publisher | MDPI |
Publisher Date | 2022-07-28 |
Access Restriction | Open |
Subject Keyword | Algorithms Social Networks Influence Spreading Information Spreading Epidemic Spreading Scalable Algorithm Pseudo-algorithm Modelling Social Networks Social Media Networks Centrality Measures Community Detection |
Content Type | Text |
Resource Type | Article |