| In recent years,the related researches about complex network have attracted extensive attention of researchers.Especially with the rapid development of social networks and the increasingly diversified types of information dissemination,this research boom has been further promoted.Existing studies often combine the basic theory of complex network with many simplified and abstract practical application scenarios.The researches based on complex networks cover a wide range,including network evolution modeling,topology empirical analysis,link prediction and information mining,etc.Among them,the studies of propagation dynamics based on complex network have attracted the attention of scholars in many fields,such as physics,computer sciences,mathematics and social sciences,etc.For example,tracing the spread of virus in crowd contact network,preventing and controlling the public opinion information in social network,relieving vehicle congestion in transportation network,troubleshooting and checking the successive failures in power network,etc.Using the relevant methods about the complex network propagation dynamics can simplify the complex propagation process in the network and facilitate the construction of propagation model,which has a certain positive influence on theoretical research and practical fit.With the popularization of mobile communication and the rapid development of Internet related technologies,the propagation of public opinion information in the network has become faster and wider.People can know more real time information quickly,but the propagation of the corresponding negative rumors has also brought a great negative influence.For example,a nuclear leak accident occurred in Japan in 2011.The false news about "iodized salt can prevent nuclear radiation" once triggered people to rush to buy iodized salt.In 2013,a few minutes after the false news that "the White House exploded and president Obama was injured"was spread in the network,and the US stocks plummeted.Since 2020,the COVID-19 virus has spread all over the world,and it caused the huge losses to people’s lives and property.All these have triggered scholars to carry out further research on the propagation rules of different types of information on complex networks.Relevant researches can provide decision-making basis for the prevention and control of rumors and diseases,the guidance of correct news,the propagation of major discoveries,and they have important practical significance.Based on the propagation theory of complex network,this paper aims at studying the propagation rules of different types of information in the network,modeling and carrying out the prevention and control research on the process of rumor propagation,behavior propagation and knowledge propagation in the complex network.The specific research contents are as follows:(1)In order to describe the propagation process of the rumor inside and outside the institution accurately,analyze the influence of internal rumors on internal and external institution,this paper combined the state changes of various types of participants inside and outside the institution caused by internal rumors,and the rumor dissemination model inside the institution and the rumor propagation model inside and outside institutions are constructed.Firstly,we proposed a new internal rumor propagation model based on the traditional rumor propagation models,which described the dynamic changes of nodes caused by internal rumor propagation in detail.Then,in order to further study the impact of internal rumors on people outside the institution,we split all the people into two institutions(inside and outside),and we constructed the rumor propagation model inside and outside institutions based on multiple types of participants.Next,the mean field equations corresponding to the two models were analyzed respectively,the basic reproduction number was obtained according to the next generation matrix method,and the local stability and global stability of the models at the rumor free equilibrium were discussed based on Jacobian matrix,Lyapunov stability theory and Lasalles invariance principle.Through numerical simulation,different factors which affected the propagation of rumors inside and outside the institution were analyzed.The above researches provided certain reference for studying the propagation of information inside and outside the institution.(2)In order to realize the prevention and control of sudden and recurrent rumors,based on the propagation characteristics of the two types of information,this paper constructed a sudden rumor control model with single life cycle and the multi-stages control model based on recurrent rumors.Based on the triggering of rumors caused by different types of events,the thinking delay and dynamic rumor propagation probability were introduced into the two models,and corresponding prevention and control strategies were established.Then,based on the Floquet impulsive equation theory and the comparison theorem,we got the conditions that reach the rumor-free state eventually for the proposed two models and the corresponding rumor-free state solution.Next,through mathematical derivation and numerical simulation experiments,the factors affecting the propagation of the two rumors are discussed,and the scheme to control the large-scale spread of the two rumors is given.At present,the COVID-19 is still spread in many countries,and the epidemic has brought serious losses to people.At the same time,the sudden rumors based on this incident have further aggravated people’s panic.After the end of the COVID-19 epidemic,and the recurrent rumors related to the COVID-19 are likely to spread again in the future.Therefore,the research in this paper may provide some references for controlling the rumors related to the COVID-19.(3)In order to analyze the influence of group behavior in the network and the behavior competition process when multiple behaviors coexist,from the perspective of behavior information propagation,we constructed a behavior propagation and confrontation competition model based on information driven which coupled behavior propagation with information propagation,and studied the propagation process of single behavior and confrontation behaviors.Compared with the traditional models,the new model introduced the individual behavior motivation,and the individual behavior motivation was quantified through the information edge weight and the length of the reachable path between individuals.Based on the proposed model,we simulated the behavior propagation process in different networks respectively,analyzed the factors affecting the behavior propagation in the network through experiments,and verified the results of theoretical derivation.Then,the real data of search behavior of MiTalk and WeChat in the stage of competitive behavior are crawled,and the error values of real curve and simulated curve are obtained based on the MSE,and the effectiveness of the model has been further verified.(4)In order to maximize the propagation of new major discoveries of COVID-19,we constructed a multi-domain knowledge propagation model based on the new major discoveries related to COVID-19 based on the factors that contributed to the mass production of COVID-19 related papers.In 2020,the COVID-19 virus spread across the globe,which caused serious losses to people’s production and life.At the same time,in addition to the continuing increment in the number of infected people,and the papers related to COVID-19 also showed a large increment in the overall number of trends.What caused this situation?By crawling the data of COVID-19-related papers from Web of Sciences in 2020,we found that there exist three mechanisms to promote the rapid growth of COVID-19 related papers:incentive mechanism,cross-field collaboration mechanism,and potential impact mechanism of writing papers.Then,combined with the above three mechanisms,and a multi-field paper association structure network was constructed to conduct research and analysis on the propagation of a major new discovery in a specific field.According to the traditional information propagation models,a multi-domain knowledge propagation model based on the new major discoveries related to COVID19 was constructed.Through theoretical derivation and experimental verification,this paper analyzed the different factors affecting the propagation of new discoveries inside a domain.The construction of this model can provide ideas for promoting the propagation of major new discoveries and help researchers understand major new discoveries in time. |
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