Information diffusion in signed networks


Autoři: Xiaochen He aff001;  Haifeng Du aff001;  Marcus W. Feldman aff001;  Guangyu Li aff001
Působiště autorů: Center for Administration and Complexity Science, Xi’an Jiaotong University, Xi’an, China aff001;  Department of Sociology, Cornell University, Ithaca, New York, United States of America aff002;  Department of Biology, Stanford University, Stanford, California, United States of America aff003
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: 10.1371/journal.pone.0224177

Souhrn

Information diffusion has been widely discussed in various disciplines including sociology, economics, physics or computer science. In this paper, we generalize the linear threshold model in signed networks consisting of both positive and negative links. We analyze the dynamics of the spread of information based on balance theory, and find that a signed network can generate path dependence while structural balance can help remove the path dependence when seeded with balanced initialized active nodes. Simulation shows that the diffusion of information based on positive links contradicts that based on negative links. More positive links in signed networks are more likely to activate nodes and remove path dependence, but they can reduce predictability that is based on active states. We also find that a balanced structure can facilitate both the magnitude and speed of information diffusion, remove the path dependence, and cause polarization.

Klíčová slova:

Centrality – Collective human behavior – Computer and information sciences – Evolutionary theory – Network analysis – Simulation and modeling – Social networks – Sociology


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PLOS One


2019 Číslo 10