Information spreading model based on cellular automaton

Abstract

The invention provides an information spreading model based on a cellular automaton, comprising the evolution rule, parameter and algorithm of the model and main technological indexes for measuring states. On such a basis, user states are divided into sever types, a rumor spreading process is analyzed and researched, and a rumor spreading mechanism is revealed according to differences of different parameter comparison results. A rumor spreading control strategy is further provided, and a great suppression effect on a final information spreading extent is achieved. Simulation of the model built based on the cellular automaton starts with microcosm to reflect macroscopic behaviors of groups, a simulation result is more intuitional, meanwhile, the model is flexible in structure, and can randomly change the control strategy during an evolutionary process, which is incomparable with a traditional differential equation model. Real data and a simulation experiment result have a relative high fitting degree, so that the built model has the actual application value, and can provide a support for making the rumor control strategy.

Description

technical field [0001] The invention belongs to the technical field of social network, and in particular relates to an information dissemination model based on a cellular machine. Background technique [0002] Since the emergence of social networks, they have experienced a rapid development process. The use of social networks to disseminate information has also become an important way for network users to communicate; a large amount of dynamic communication information affects the decision-making of network members, and systematically and scientifically analyzes social networks. The behavior of information dissemination will enable us to have a further understanding of the grid structure, attributes and laws followed by emergencies from the perspective of information dissemination. [0003] The vigorous development of social networks has made the release and reception of information extremely simple and fast. Information is spread in the form of "nuclear fission". Once a mes...

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Problems solved by technology

There are also research models based on differential equations to analyze the law of information propagation, but the solution of the equation is extremely sensitive to the initial conditions; the propagation model based on dynamics, by referring to the successful application of complex network theory in other network research, parameter quantification is difficult

Although these communication models have been expanded and studied in many networks, the research on network information dissemination is still at a relatively early stage, and a complete basic theory and method of social network and information dissemination have not been proposed, and the analysis of the nature is still Limited to qualitative or semi-quantitative statistics

[0005] Most of the traditional propagation models are based on rule-based network research, and generally have the following shortcomings: (1) they do not take into account the real status of users in online social networking sites, such as the probability of repeated infection or infection; (2) the calculation is complex , the parameters cannot be adjusted at any time during the evolution process; (3) There are few divided user states, and the information dissemination process in the social network cannot be fully and objectively described; (4) The simulation results are not intuitive, and the behavioral characteristics of the information dissemination process cannot be well described

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