Method for simulating rumor propagation and related equipment

Abstract

The invention provides a method for simulating rumor propagation, which is characterized by comprising the following steps of: establishing a first rumor propagation model with a natural birth and death probability; simplifying the first rumor propagation model to obtain a second rumor propagation model; and simulating rumor propagation by using the second rumor propagation model. According to the embodiment of the invention, the latent state and the reverse state are introduced, so that more real description of rumor propagation dynamics, particularly delay between exposure and propagation, an anti-rumor effect and birth rate and death rate in a simulation process are provided, the method can be more flexibly adapted to changes of nodes in an actual social network, and the simulation efficiency is improved. The invention also provides a strategy for effectively controlling rumor propagation, such as promoting anti-rumor propagation or intervening in a latent state individual before a node becomes an active propagator.

Description

Technical Field

[0001] The present application relates to the technical field of social network modeling and analysis, and in particular to a method for simulating rumor propagation and related equipment. Background Art

[0002] With the rapid development of online social networks, the spread of information (including rumors) has become increasingly common. Rumors often contain false or misleading information and can lead to serious social and economic consequences. Therefore, understanding and controlling the spread of rumors is crucial to maintaining social stability.

[0003] Information propagation in online social networks combines the research of complex networks, infectious disease dynamics, etc. As the core of information propagation analysis, the main task of the propagation model is to fully consider various factors that affect information propagation in order to understand, simulate and predict the process of information propagation.

[0004] However, although existing models provide a basic framework for understanding rumor propagation, they have some limitations. Existing models fail to consider the latency of nodes after being exposed to information. When a node is exposed to rumor information, it does not respond immediately, but enters a latent state. After a period of time, the node may or may not spread the rumor information. Existing models usually do not consider the influence of nodes that actively refute rumors, which may significantly change the dynamics of rumor propagation. Existing models do not consider the addition and disappearance of nodes in the network. Summary of the invention

[0005] In view of this, the purpose of this application is to propose a method for simulating the spread of rumors and related equipment.

[0006] Based on the above objectives, the present application provides a method for simulating rumor propagation, including:

[0007] Establish the first rumor propagation model with natural birth and death probabilities;

[0008] Simplifying the first rumor propagation model to obtain a second rumor propagation model;

[0009] The second rumor propagation model is used to simulate rumor propagation.

[0010] In one possible implementation, the propagation nodes in the first rumor propagation model include: susceptible nodes, latent nodes, refutation nodes, infected nodes and recovery nodes; the susceptible nodes represent nodes that have not yet been exposed to the information; the latent nodes represent nodes that have received the information but have not responded immediately; the refutation nodes represent nodes that spread information opposite to the rumor information in order to persuade neighboring nodes to stop spreading the rumor information; the infected nodes represent nodes that are spreading rumor information; and the recovery nodes represent nodes that have lost interest in spreading rumors.

[0011] In a possible implementation, the step of establishing a first rumor propagation model with a probability of natural death includes:

[0012] Setting the naturally born number of said susceptible nodes;

[0013] In response to a susceptible node contacting an infected node, the susceptible node believes the rumor and is transformed into the latent node with a first probability; or, the susceptible node does not believe the rumor and persuades other infected nodes to stop spreading the rumor with a second probability; or, the susceptible node is not interested in the rumor, does not spread the rumor and does not persuade others, and becomes the recovery node with a third probability;

[0014] In response to the latent node passing the first time, deciding to spread the rumor and become the infected node with a fourth probability; or deciding not to spread the rumor and become the recovery node with a fifth probability;

[0015] In response to one of the infected nodes contacting one of the refutation nodes, the infected node becomes the recovery node with a sixth probability;

[0016] In response to an infected node losing interest in the rumor, forgetting the rumor, or stopping spreading the rumor after a second period of time, and becoming the recovery node with a seventh probability;

[0017] In response to a refuted node expiring a third time, it is transformed into the recovery node with an eighth probability.

[0018] In a possible implementation, the susceptible nodes, the latent nodes, the refutation nodes, the infected nodes, and the recovery nodes in the first rumor propagation model all have a probability of natural death.

[0019] In a possible implementation, simplifying the first rumor propagation model to obtain a second rumor propagation model includes:

[0020] The number of nodes in susceptible, latent, refuted, infected and recovered states is described using mean field equations;

[0021] The mean field equation is simplified.

[0022] In a possible implementation, the method further includes:

[0023] Obtaining the basic reproduction number of the second rumor propagation model;

[0024] In response to the basic reproduction number being less than 1, the rumor-free equilibrium point of the second rumor propagation model is locally asymptotically stable and globally asymptotically stable.

[0025] Based on the same inventive concept, the embodiment of the present application also provides a device for simulating rumor propagation, including:

[0026] A building module configured to build a first rumor propagation model with natural birth and death probabilities;

[0027] A simplification module, configured to simplify the first rumor propagation model to obtain a second rumor propagation model;

[0028] The simulation module is configured to simulate the spread of rumors using the second rumor propagation model.

[0029] Based on the same inventive concept, an embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a method for simulating rumor propagation as described in any one of the above is implemented.

[0030] Based on the same inventive concept, an embodiment of the present application also provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable the computer to execute any of the above-mentioned methods of simulating rumor propagation.

[0031] Based on the same inventive concept, an embodiment of the present application also provides a computer program product, which includes computer program instructions, and the computer instructions are used to enable the computer program product to execute any of the above-mentioned methods for simulating rumor propagation.

[0032] From the above, it can be seen that the method and related equipment for simulating rumor propagation provided by the present application establish a first rumor propagation model with natural birth and death probabilities; simplify the first rumor propagation model to obtain a second rumor propagation model; and use the second rumor propagation model to simulate rumor propagation. The embodiment of the present application provides a more realistic description of the dynamics of rumor propagation by introducing latent and refutation states, especially the delay between exposure and propagation and the role of anti-rumors, as well as the inclusion of birth and death rates in the simulation process. It can more flexibly adapt to changes in nodes in actual social networks, and also provides strategies for effectively controlling the spread of rumors, such as promoting the spread of anti-rumors or intervening in latent individuals before nodes become active communicators. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the present application or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0034] Figure 1 A schematic diagram of a method flow chart for simulating rumor propagation according to an embodiment of the present application;

[0035] Figure 2 This is a schematic diagram of the susceptible-latent-refuted-infected-recovered model of an embodiment of the present application;

[0036] Figure 3 This is a schematic diagram of the structure of a device for simulating rumor propagation according to an embodiment of the present application;

[0037] Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0038] In order to make the objectives, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0039] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should be the usual meanings understood by people with ordinary skills in the field to which the present application belongs. The "first", "second" and similar words used in the embodiments of the present application do not represent any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing in front of the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0040] It is understandable that before using the technical solutions of each embodiment of the present disclosure, the type, scope of use, usage scenarios, etc. of the personal information involved will be informed to the user in an appropriate manner, and the user's authorization will be obtained.

[0041] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly remind the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can independently choose whether to provide personal information to software or hardware such as an electronic device, application, server, or storage medium that performs the operation of the technical solution of the present disclosure according to the prompt message.

[0042] As an optional but non-limiting implementation, in response to receiving the user's active request, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0043] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0044] As mentioned in the background technology section, with the rapid development of online social networks, the spread of information (including rumors) has become more and more common. Rumors often contain false or misleading information and can lead to serious social and economic consequences. Therefore, understanding and controlling the spread of rumors is crucial to maintaining social stability.

[0045] Information propagation in online social networks combines the research of complex networks, infectious disease dynamics, etc. As the core of information propagation analysis, the main task of the propagation model is to fully consider various factors that affect information propagation in order to understand, simulate and predict the process of information propagation.

[0046] However, although existing models provide a basic framework for understanding rumor propagation, they have some limitations. Existing models fail to consider the latency of nodes after being exposed to information. When a node is exposed to rumor information, it does not respond immediately, but enters a latent state. After a period of time, the node may or may not spread the rumor information. Existing models usually do not consider the influence of nodes that actively refute rumors, which may significantly change the dynamics of rumor propagation. Existing models do not consider the addition and disappearance of nodes in the network.

[0047] Taking the above into consideration, the embodiment of the present application proposes a method for simulating the spread of rumors, by establishing a first rumor propagation model with natural birth and death probabilities; simplifying the first rumor propagation model to obtain a second rumor propagation model; and using the second rumor propagation model to simulate the spread of rumors. The embodiment of the present application provides a more realistic description of the dynamics of rumor propagation by introducing latent and refutation states, especially the delay between exposure and propagation and the role of anti-rumors, as well as the birth and death rates included in the simulation process, which can more flexibly adapt to the changes of nodes in actual social networks, and also provides strategies for effectively controlling the spread of rumors, such as promoting the spread of anti-rumors or intervening in latent individuals before the nodes become active communicators. The embodiments of the present application can contribute to the spread of anti-rumors by simulating the process of rumor propagation, and can more clearly define the propagation path and methods of rumors, thereby more effectively preventing the spread of rumors.

[0048] The technical solutions of the embodiments of the present application are described in detail below through specific examples.

[0049] refer to Figure 1 The method for simulating rumor propagation in the embodiment of the present application comprises the following steps:

[0050] Step S101, establishing a first rumor propagation model with natural birth and death probabilities;

[0051] Step S102, simplifying the first rumor propagation model to obtain a second rumor propagation model;

[0052] Step S103: simulating rumor propagation using the second rumor propagation model.

[0053] With respect to step S101, in some embodiments, the propagation nodes in the first rumor propagation model include: susceptible nodes, latent nodes, refutation nodes, infected nodes and recovery nodes; the susceptible nodes represent nodes that have not yet been exposed to the information; the latent nodes represent nodes that have received the information but have not responded immediately; the refutation nodes represent nodes that spread information contrary to the rumor information in order to persuade neighboring nodes to stop spreading the rumor information; the infected nodes represent nodes that are spreading the rumor information; and the recovery nodes represent nodes that have lost interest in spreading the rumor.

[0054] In some embodiments, the establishment of a first rumor propagation model with a natural death probability includes: setting the number of susceptible nodes to be naturally born; in response to a susceptible node contacting an infected node, the susceptible node believes the rumor and is transformed into the latent node with a first probability; or, the susceptible node does not believe the rumor and persuades other infected nodes to stop spreading the rumor with a second probability; or, the susceptible node is not interested in the rumor, does not spread the rumor and does not persuade others, and becomes the recovery node with a third probability; in response to the latent node passing a first time, deciding to spread the rumor and becoming an infected node with a fourth probability; or, deciding not to spread the rumor and becoming the recovery node with a fifth probability; in response to an infected node contacting a refutation node, the infected node becomes the recovery node with a sixth probability; in response to an infected node passing a second time, losing interest in the rumor, forgetting the rumor or stopping spreading the rumor, and becoming the recovery node with a seventh probability; in response to a refuted node passing a third time, transforming into the recovery node with an eighth probability.

[0055] In some embodiments, the susceptible nodes, the latent nodes, the refutation nodes, the infected nodes and the recovery nodes in the first rumor propagation model all have a probability of natural death.

[0056] refer to Figure 2 , which is a schematic diagram of the susceptible-latent-refuted-infected-recovered model of an embodiment of the present application.

[0057] In this embodiment, a Susceptible-Latent-Confuted-Infected-Recovered (SLCIR) model is proposed. In this model, five types of nodes are included: (1) Susceptible nodes (S) represent nodes that have not yet been exposed to information; (2) Latent nodes (L) represent nodes that have received information but have not responded immediately; (3) Confuted nodes (C) represent nodes that spread information contrary to the rumor information in order to persuade neighboring nodes to stop spreading the rumor information; (4) Infected nodes (I) represent nodes that are currently spreading rumor information; (5) Recovered nodes (R) represent nodes that have lost interest in spreading rumors. The state transitions between different node types in the SLCIR model are as follows: Figure 2 As shown:

[0058] There is a naturally occurring number of susceptible nodes (A) in the graph.

[0059] When a susceptible node comes into contact with an infected node, the susceptible node may transform into one of three types:

[0060] It believes the rumor and becomes a latent node with probability α (first probability);

[0061] It does not believe the rumor and persuades other infected nodes to stop spreading the rumor with probability β (second probability);

[0062] It is not interested in rumors, does not spread rumors or persuade others, and therefore becomes a recovery node with probability γ (the third probability).

[0063] A latent node may transform into one of two types:

[0064] It decides to spread the rumor and becomes an infected node with probability ω (the fourth probability);

[0065] It decides not to spread the rumor and takes the probability (Fifth probability) Become a recovery node.

[0066] When an infected node contacts a refutation node, it will become a recovery node with probability θ (sixth probability).

[0067] When an infected node may lose interest or forget the rumor, stop spreading the rumor, and become a recovery node with probability ξ (seventh probability).

[0068] A refuted node will transform into a recovery node with probability μ (eighth probability) after a long time.

[0069] Each node has a natural death probability of d.

[0070] With respect to step S102, in some embodiments, the first rumor propagation model is simplified to obtain a second rumor propagation model, including: using the mean field equation to describe the number of nodes in a susceptible state, a latent state, a refuted state, an infected state, and a recovered state; and simplifying the mean field equation.

[0071] In this embodiment, let S(t), L(t), C(t), I(t) and R(t) represent the number of nodes in susceptible state, latent state, refuted state, infected state and recovered state at time t respectively.

[0072] The mean field equation of the SLCIR model is expressed as follows:

[0073]

[0074] in,

[0075] Since the restored state node will not change to other states, the mean field equation can be simplified to the following formula:

[0076]

[0077] In the early stage of information dissemination, SLCIR assumes that most nodes are susceptible nodes and only a few nodes are disseminators. At t = 0, the number of each type of node in the dissemination model is as follows:

[0078]

[0079] Therefore, at t = 0, the rumor-free equilibrium point of the SLCIR model is S 0 ,L 0 ,C 0 ,I 0 They represent the number of nodes in susceptible, latent, refuted, and infected states at time 0. According to the rumor-free equilibrium point P 0 , considering the possibly infected type nodes as L and I type nodes, the growth rate function h(x) of the possibly infected type nodes is as follows:

[0080]

[0081] The decay rate function g(x) of the infected type node is as follows:

[0082]

[0083] At the rumor-free equilibrium point P 0At , the deviation equations of h(x) and g(x) for L-type and I-type nodes are:

[0084]

[0085] According to the above two deviation equations, the regeneration matrix FV -1 As described in the following formula:

[0086]

[0087] In some embodiments, the method further includes: obtaining a basic reproduction number of the second rumor propagation model; in response to the basic reproduction number being less than 1, the rumor-free equilibrium point of the second rumor propagation model is locally asymptotically stable and globally asymptotically stable.

[0088] In this embodiment, the basic reproduction number R0 is equal to the spectral radius of the reproduction matrix:

[0089]

[0090] Local and global asymptotic stability are proven in the following way:

[0091] Theorem 1. If R 0 <1, then there is no rumor equilibrium point P 0 is locally asymptotically stable.

[0092] Proof: When R 0 <1, the system has only one equilibrium point P without rumor spreading. 0 The simplified Jacobian matrix of the equilibrium field equation is calculated as follows:

[0093]

[0094] Will Substituting into the above formula, we can get the Jacobian matrix value of the rumor disappearance equilibrium point as follows:

[0095]

[0096] The matrix characteristic polynomial shown above should be equal to zero:

[0097]

[0098] The parameters in the above formula are simplified by using the parameters in the following formula:

[0099]

[0100] The simplified formula is:

[0101]

[0102] By calculating the matrix determinant from the above formula, we can get the following formula:

[0103]

[0104] The solution of the above equation is: λ1=-d<0,λ2=-a2<0, and the roots of the following equation are:

[0105] make: Then 2 +b1λ+b2=0 and

[0106] From this we can get, Obviously, λ4<0, because R0<1, so In addition, due to Therefore, λ3<0.

[0107] So far, all eigenvalues ​​have been found to be less than 0. According to the Routh-Hurwitz stability criterion, it is proved that when R0<1, the rumor-free equilibrium point P of the SLCIR model 0 Locally asymptotically stable.

[0108] Theorem 2. If R0<1, then the rumor-free equilibrium point P of the SLCIR model is 0 is globally asymptotically stable.

[0109] Proof: To study P 0 The global asymptotic stability of 0 A Lyapunov function V(t) is constructed:

[0110] V(t)=ωL(t)+a1I(t)

[0111] The time derivative of V(t) can be calculated as follows:

[0112] V′(t)=ωL′(t)+a1I′(t)=ω[αS(t)I(t)-a1L(t)]+a1[ωL(t)-θI(t)C(t)-a3I(t)]

[0113] =αωS(t)I(t)-a1a3I(t)-a1θI(t)C(t)

[0114] From S(t)≥0, we know that A-a4S(t)I(t)-dS(t)≥0, so Right now From the basic reproduction number and the above parameter list, we can see that From R0<1, we can infer that Therefore, V′(t)<0. According to the Lasalle invariant set principle, when R0<1, the rumor-free equilibrium point P of the SLCIR model is 0 is globally asymptotically stable.

[0115] It can be seen from the above embodiments that the method for simulating rumor propagation described in the embodiments of the present application is to establish a first rumor propagation model with natural birth and death probabilities; simplify the first rumor propagation model to obtain a second rumor propagation model; and use the second rumor propagation model to simulate rumor propagation. The embodiments of the present application provide a more realistic description of the dynamics of rumor propagation by introducing latent and refutation states, especially the delay between exposure and propagation and the role of anti-rumors, as well as the birth rate and death rate included in the simulation process, which can more flexibly adapt to the changes of nodes in actual social networks, and also provide strategies for effectively controlling the spread of rumors, such as promoting the spread of anti-rumors or intervening in latent individuals before the nodes become active communicators. The embodiments of the present application can contribute to the spread of anti-rumors by simulating the process of rumor propagation, and can more clearly define the propagation path and methods of rumors, thereby more effectively preventing the spread of rumors.

[0116] It should be noted that the method of the embodiment of the present application can be performed by a single device, such as a computer or server. The method of this embodiment can also be applied to a distributed scenario and completed by multiple devices cooperating with each other. In the case of such a distributed scenario, one of the multiple devices can only perform one or more steps in the method of the embodiment of the present application, and the multiple devices will interact with each other to complete the described method.

[0117] It should be noted that the above describes some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0118] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a device for simulating the spread of rumors.

[0119] refer to Figure 3 , the device for simulating rumor propagation comprises:

[0120] Establishing module 31, configured to establish a first rumor propagation model with natural birth and death probabilities;

[0121] A simplification module 32 is configured to simplify the first rumor propagation model to obtain a second rumor propagation model;

[0122] The simulation module 33 is configured to simulate rumor propagation using the second rumor propagation model.

[0123] For the convenience of description, the above device is described in terms of functions divided into various modules. Of course, when implementing the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0124] The device of the above embodiment is used to implement the corresponding method of simulating rumor propagation in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0125] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments, the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for simulating rumor propagation described in any of the above embodiments is implemented.

[0126] Figure 4 A more specific schematic diagram of the hardware structure of an electronic device provided in this embodiment is shown, and the device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are connected to each other through the bus 1050 in the device.

[0127] The processor 1010 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0128] The memory 1020 may be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 may store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program codes are stored in the memory 1020 and are called and executed by the processor 1010.

[0129] The input / output interface 1030 is used to connect the input / output module to realize information input and output. The input / output module can be configured in the device as a component (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

[0130] The communication interface 1040 is used to connect a communication module (not shown) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired mode (such as USB, network cable, etc.) or a wireless mode (such as mobile network, WIFI, Bluetooth, etc.).

[0131] The bus 1050 includes a path that transmits information between the various components of the device (eg, the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040).

[0132] It should be noted that, although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040 and the bus 1050, in the specific implementation process, the device may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the above device may also only include the components necessary for implementing the embodiments of the present specification, and does not necessarily include all the components shown in the figure.

[0133] The electronic device of the above embodiment is used to implement the corresponding method of simulating rumor propagation in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0134] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method of simulating rumor propagation as described in any of the above embodiments.

[0135] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0136] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the method of simulating rumor propagation as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0137] Based on the same inventive concept, corresponding to the method for simulating rumor propagation described in any of the above embodiments, the present disclosure also provides a computer program product, which includes computer program instructions. In some embodiments, the computer program instructions can be executed by one or more processors of a computer so that the computer and / or the processor execute the method for simulating rumor propagation. Corresponding to the execution subject corresponding to each step in each embodiment of the method for simulating rumor propagation, the processor that executes the corresponding step may belong to the corresponding execution subject.

[0138] The computer program product of the above embodiment is used to enable the computer and / or the processor to execute the method of simulating rumor propagation as described in any of the above embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0139] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application (including the claims) is limited to these examples. In line with the concept of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0140] In addition, to simplify the description and discussion, and in order not to make the embodiments of the present application difficult to understand, the known power supply / ground connection with the integrated circuit (IC) chip and other components may or may not be shown in the provided drawings. In addition, the device can be shown in the form of a block diagram to avoid making the embodiments of the present application difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform to be implemented in the embodiments of the present application (that is, these details should be fully within the scope of understanding of those skilled in the art). In the case of elaborating specific details (e.g., circuits) to describe exemplary embodiments of the present application, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details or when these specific details are changed. Therefore, these descriptions should be considered to be illustrative rather than restrictive.

[0141] Although the present application has been described in conjunction with specific embodiments of the present application, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0142] The embodiments of the present application are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included in the scope of protection of the present application.

Claims

1. A method for simulating rumor propagation, characterized in that: include: Establish the first rumor propagation model with natural birth and death probabilities; Simplifying the first rumor propagation model to obtain a second rumor propagation model; The second rumor propagation model is used to simulate rumor propagation.

2. The method according to claim 1, characterized in that The propagation nodes in the first rumor propagation model include: susceptible nodes, latent nodes, refutation nodes, infected nodes and recovery nodes; the susceptible nodes represent nodes that have not yet been exposed to the information; the latent nodes represent nodes that have received the information but have not responded immediately; the refutation nodes represent nodes that spread information opposite to the rumor information in order to persuade neighboring nodes to stop spreading the rumor information; the infected nodes represent nodes that are spreading rumor information; and the recovery nodes represent nodes that have lost interest in spreading rumors.

3. The method according to claim 2, characterized in that The first rumor propagation model with a probability of natural death is established, including: Setting the naturally born number of said susceptible nodes; In response to a susceptible node contacting an infected node, the susceptible node believes the rumor and is transformed into the latent node with a first probability; or, the susceptible node does not believe the rumor and persuades other infected nodes to stop spreading the rumor with a second probability; or, the susceptible node is not interested in the rumor, does not spread the rumor and does not persuade others, and becomes the recovery node with a third probability; In response to the latent node passing the first time, deciding to spread the rumor and become the infected node with a fourth probability; or deciding not to spread the rumor and become the recovery node with a fifth probability; In response to one of the infected nodes contacting one of the refutation nodes, the infected node becomes the recovery node with a sixth probability; In response to an infected node losing interest in the rumor, forgetting the rumor, or stopping spreading the rumor after a second period of time, and becoming the recovery node with a seventh probability; In response to a refuted node expiring a third time, the node is transformed into the recovery node with an eighth probability.

4. The method according to any one of claims 1 to 3, characterized in that: The susceptible nodes, the latent nodes, the refutation nodes, the infected nodes and the recovery nodes in the first rumor propagation model all have a probability of natural death.

5. The method according to claim 1, characterized in that The step of simplifying the first rumor propagation model to obtain a second rumor propagation model includes: The number of nodes in susceptible, latent, refuted, infected and recovered states is described using mean field equations; The mean field equation is simplified.

6. The method according to claim 1, characterized in that The method further comprises: Obtaining the basic reproduction number of the second rumor propagation model; In response to the basic reproduction number being less than 1, the rumor-free equilibrium point of the second rumor propagation model is locally asymptotically stable and globally asymptotically stable.

7. A device for simulating rumor spreading, characterized in that: include: A building module configured to build a first rumor propagation model with natural birth and death probabilities; A simplification module, configured to simplify the first rumor propagation model to obtain a second rumor propagation model; The simulation module is configured to simulate the spread of rumors using the second rumor propagation model.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 6.

10. A computer program product, comprising computer program instructions, which, when executed on a computer, cause the computer to execute the method according to any one of claims 1 to 6.

Images