Analysis of the Influence of Individual Web Behavior Pattern on Group Behavior Simulation

Li, Jingjing; Liu, Yang; Liu, Hongri; Wang, Bailing; Wang, Wei; Wang, Lianhai

doi:10.1109/dsc.2019.00071

Cited by 1 publication

(1 citation statement)

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“…Finally, analyze the trouble. By comparing different troubles and ordinary events, the network rules of other Posting methods are studied, and the behaviour rules of users are statistically analyzed based on the Posting and reply rules of users [18]. This paper provides a framework for analyzing QQ users' human behaviour patterns and social structure patterns and conducts empirical analysis based on QQ data to reveal the rules of QQ users' human behaviour patterns in the period of emergencies.…”

Section: Introductionmentioning

confidence: 99%

Human Emergency Behaviour Characteristics in Large-scale Emergencies Based on Mobile Communication Data

Wei

Luo

Chen

et al. 2021

Preprint

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The characteristics of human emergency behaviour under the emergency are a crucial scientific issue in basic emergency management research. The analysis of time dynamic aspects of human behaviour based on electronic footprint data provides a new method for quantitative investigation of this problem. Previous studies generally assumed that human behaviours were randomly distributed in time, but few studies studied the impact of emergencies and carried out prediction methods through social media data. Using mobile QQ space communication data, this paper from four kinds of emergencies and one kind of conventional event data, digging out the statistical characteristic on the time dimension of human communication behaviour, and in case of any emergencies, such as public security mode of evolution, to explore intrinsic emergency regularity of the impact of human communication behaviour model and further predict human behaviour characteristics. We found that the communication peaks accompanying an emergency are local in time, resulting in a communication avalanche that importantly engages eyewitness social networks. In mobile QQ space communication, the probability distribution of the interval time of the Posting behaviour sequence shows the statistical characteristics of power-law and approximate exponential tail. Compared with most of the typical Posting behaviour, the probability distribution of the interval time of the Posting behaviour sequence is higher. At the same time, the mnemonic is lower than most of the typical Posting behaviour, with a weak anti- mnemonic. These results are theoretically helpful in understanding the regularity of the impact of emergencies on human communication behaviour patterns and have potential application value in predicting the impact degree of crises and the analysis and classification of human social attributes.

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Section: Introductionmentioning

confidence: 99%