CN109657139B - Simulation method, device and equipment for network event propagation - Google Patents
Simulation method, device and equipment for network event propagation Download PDFInfo
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- CN109657139B CN109657139B CN201811507486.2A CN201811507486A CN109657139B CN 109657139 B CN109657139 B CN 109657139B CN 201811507486 A CN201811507486 A CN 201811507486A CN 109657139 B CN109657139 B CN 109657139B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
- H04L51/52—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail for supporting social networking services
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- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/01—Social networking
Abstract
The invention provides a simulation method, a simulation device and simulation equipment for network event propagation, which relate to the technical field of computers, and the method comprises the steps of acquiring a network event and the attribute of the network event; the attributes include at least one of: time, type, or subject; acquiring the node attribute of the current node, and calculating emotional attitude information according to the attribute of the network event and the node attribute and the historical emotional attitude information of the previous node; determining emotion deviation information of the current node to the network event according to the emotion attitude information; the emotional bias information is any one of the following: supportive, anti-or neutral; propagating the network event to the neighboring node if the emotional bias information is supporting or opposing; and if the emotional bias information is neutral, finishing the propagation of the network event at the current node. The method improves the accuracy of information transmission process simulation by adding the calculation of the emotional attitude information, and is more suitable for practical application.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a method, an apparatus, and a device for simulating network event propagation.
Background
With the popularization of the internet, people increasingly depend on the network to transmit and obtain public opinion information. Social networking services, in particular, have rapidly developed in recent years, and they extend people's social range from real interpersonal relationships to virtual networks by virtue of strong network connectivity. The social range of people is gradually expanded through network applications such as instant chat tools, microblogs, blogs and network communities, and finally a huge complex network associated with people is formed. The existing network event propagation related model is mainly based on a complex network, modeling is carried out by applying knowledge of computer theory, and the simulation of information propagation is too simple to be put into practical application.
Disclosure of Invention
In view of the above, an object of the present invention is to provide a method, an apparatus and a device for simulating network event propagation, so as to more accurately simulate a network event.
In a first aspect, an embodiment of the present invention provides a method for simulating network event propagation, where the method includes: acquiring a network event and the attribute of the network event; the attributes include at least one of: time, type, or subject; acquiring the node attribute of the current node, and calculating the emotional attitude information of the current node according to the historical emotional attitude information of the previous node, the attribute of the network event and the node attribute; determining emotion deviation information of the current node to the network event according to the emotion attitude information; the emotional bias information is any one of the following: supportive, anti-or neutral; propagating the network event to the neighboring node if the emotional bias information is supporting or opposing; and if the emotional bias information is neutral, finishing the propagation of the network event at the current node.
With reference to the first aspect, an embodiment of the present invention provides a first possible implementation manner of the first aspect, where before the step of obtaining a node attribute of a current node, and calculating emotional attitude information of the current node according to historical emotional attitude information of a previous node, an attribute of a network event, and the node attribute, the method further includes: judging whether the current node is in an immune area of the network event or not according to the attribute of the network event and the attribute of the node, wherein the node in the immune area can shield the network event; and if not, calculating the emotional attitude information.
With reference to the first aspect, an embodiment of the present invention provides a second possible implementation manner of the first aspect, where the step of obtaining the network event and the attribute of the network event includes: acquiring a network event; attributes of the network event are matched for the current node in an event attribute database.
With reference to the first aspect, an embodiment of the present invention provides a third possible implementation manner of the first aspect, where the step of obtaining a node attribute of a current node, and calculating emotional attitude information of the current node according to historical emotional attitude information of a previous node, an attribute of a network event, and the node attribute includes: matching node attributes for the current node in a node attribute database; the node attributes include at least: node identification, node immunity, node propagation and topic sensitivity; determining the theme sensitivity of the current node to the network event according to the node attribute and the attribute of the network event; acquiring historical emotional attitude information of a previous node; and calculating the emotional attitude information of the current node according to the historical emotional attitude information and the theme sensitivity.
With reference to the first aspect, an embodiment of the present invention provides a fourth possible implementation manner of the first aspect, where the step of determining, according to the emotional attitude information, emotional bias information of the current node to the network event includes: segmenting the value of the emotional attitude information to obtain a segmentation result; and determining the emotional deviation information of the current node to the network event according to the segmentation result.
With reference to the first aspect, an embodiment of the present invention provides a fifth possible implementation manner of the first aspect, where the emotional bias information is supporting or opposing, and the step of propagating the network event to the neighboring node includes: acquiring the propagation probability of a network event between a current node and a next node; and propagating the network event to the adjacent nodes according to the propagation probability.
With reference to the first aspect or any one of its possible implementations, an embodiment of the present invention provides a sixth possible implementation of the first aspect, where the method further includes: respectively calculating emotional attitude information of all nodes in the network, and determining emotional deviation information of all nodes to the network event according to the emotional attitude information; and generating the overall emotion deviation distribution information of the network according to the emotion deviation information of all the nodes.
In a second aspect, an embodiment of the present invention further provides a simulation apparatus for network event propagation, including:
the event acquisition module is used for acquiring the network event and the attribute of the network event; the attributes include at least one of: time, type, or subject; the computing module is used for acquiring the node attribute of the current node and computing the emotional attitude information of the current node according to the historical emotional attitude information of the previous node, the attribute of the network event and the node attribute; the emotion deviation module is used for determining emotion deviation information of the current node to the network event according to the emotion attitude information; the emotional bias information is any one of the following: supportive, anti-or neutral; the control module is used for propagating the network event to the adjacent nodes if the emotional deviation information is supporting or resisting; and the control module is also used for ending the propagation of the network event at the current node if the emotional bias information is neutral.
With reference to the second aspect, an embodiment of the present invention provides a first possible implementation manner of the second aspect, where the apparatus further includes an immune region determining module, configured to: and judging whether the current node is in an immune area of the network event or not according to the attribute of the network event and the attribute of the node, wherein the node in the immune area can shield the network event. Nodes in the immune area can shield network events; and if not, calculating the emotional attitude information.
In a third aspect, an embodiment of the present invention further provides an electronic device, including: a memory in which a computer program is stored, the computer program being executable on the processor, and a processor, the processor implementing the steps of any of the methods of the first aspect when executing the computer program.
The embodiment of the invention has the following beneficial effects: the embodiment of the invention provides a method, a device and equipment for simulating network event propagation, wherein the method comprises the steps of obtaining the attribute of a network event and the node attribute of a current node after the current node obtains the network event, calculating the emotional attitude information of the current node to the network event according to the attribute of the network event and the node attribute, and obtaining the emotional deviation information of the current node by calculating the emotional attitude information: supporting, resisting or neutralizing, if the emotional bias information is resisting or supporting, continuing to propagate the network event, and if the emotional bias information is neutralizing, stopping the propagation of the network event at the current node. The embodiment of the invention improves the accuracy of information transmission process simulation by adding the calculation of the emotional attitude information, and is more suitable for practical application.
Additional features and advantages of the disclosure will be set forth in the description which follows, or in part may be learned by the practice of the above-described techniques of the disclosure, or may be learned by practice of the disclosure.
In order to make the aforementioned objects, features and advantages of the present disclosure more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a simulation method for network event propagation according to an embodiment of the present invention;
fig. 2 is a data flow diagram of a simulation method for network event propagation according to an embodiment of the present invention;
fig. 3 is a block diagram of a simulation apparatus for network event propagation according to an embodiment of the present invention;
fig. 4 is another block diagram of a simulation apparatus for network event propagation according to an embodiment of the present invention;
fig. 5 is a block diagram schematically illustrating a structure of an electronic device according to an embodiment of the present invention.
Icon:
31-an event acquisition module; 32-a calculation module; 33-emotion bias module; 34-a control module; 35-immune region judgment module; 41-a memory; 42-processor.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
At present, the existing network event propagation model is mainly based on a complex network, and is modeled by applying knowledge of computer theory: such as a regular network, a random network, a scale-free network, etc., the simulation of information propagation is too simple, and the simulation result is far from the actual progress of the object, so that the simulation is difficult to be put into practical application. The simulation of information propagation in a network diagram mode has intuitiveness, but a network model for performing propagation simulation only depends on probability, only a network is simulated in a relatively independent space, the simulation cannot be adapted to the complex environment in the actual Internet world, and the simulation of event propagation only depends on the mode is unreliable.
Based on this, the method, the device and the equipment for simulating the network event propagation provided by the embodiment of the invention can simulate the network event more accurately.
For the convenience of understanding the present embodiment, a detailed description will be first given of a simulation method for network event propagation disclosed in the present embodiment.
Example 1
An embodiment 1 of the present invention provides a method for simulating network event propagation, which is described with reference to a flow chart of the method for simulating network event propagation shown in fig. 1, and the method includes the following steps:
step S102, acquiring a network event and the attribute of the network event; the attributes include at least one of: time, type, or subject.
The network event refers to information that is transmitted over the network, and may be text information, video information, audio information, picture information, and the like. The attribute of the network event is used for describing the network event, and at least comprises the time of occurrence of the network event, the type of the network event or the subject of the network event, and the like. The unit of time in the present invention may be seconds, minutes, hours, months, or the like, and each second in the simulation corresponds to a certain time length of the real world, for example, each second of the simulation corresponds to one day of real propagation. The types in the present invention may be: rumors, terrorism, or group activities, etc., which may be classified according to the content of the network event. The subject matter in the present invention may be: social security, political news, religious events or food security and the like, and the topics can be divided according to the influence of the network events on various aspects of the society.
And step S104, acquiring the node attribute of the current node, and calculating the emotional attitude information of the current node according to the historical emotional attitude information of the previous node, the attribute of the network event and the node attribute.
A node is a transit mechanism for network events. The user can be a personal account in the process of propagating the network event, such as the personal account in a social platform. The node attributes are used for describing information such as identification, immunity, emotional attitude information and propagation capacity of the nodes. The node attributes are stored via a node attribute database. When the node attribute is updated, the data in the node attribute database is updated. The historical emotional attitude information is the emotional attitude information of the network events with different attributes, which are propagated once by the nodes and can be acquired from the node attribute database. The attitude of the current node to the network event can be inquired according to the attribute of the network event and the attribute of the current node, and the emotional attitude information of the current node to the network event can be obtained according to the attitudes of the current node and the previous node to the network event. Step S104 considers the influence of the previous node on the emotional attitude information of the network event, so that the simulation of network propagation is more practical.
The topic sensitivities of the current node to network events of different attributes can be matched according to the attributes of the network events. And obtaining historical emotional attitude information of the previous node on the network event by inquiring the attribute of the previous node, and calculating the emotional attitude information of the current node according to the theme sensitivity of the current node on the network event and the historical emotional attitude information of the previous node on the network event. And if the current node is the first node of the network, the historical emotion of the last node on the network event is 0.
Step S106, determining emotion deviation information of the current node to the network event according to the emotion attitude information; the emotional bias information is any one of the following: supportive, objectionable or neutral.
The emotional attitude information is attitude evaluation of the nodes on the network events. The node has a larger value range of the emotional attitude information due to different attitudes of different network events, and the emotional attitude information with a close value range can be classified according to the value of the emotional attitude information to obtain emotional deviation information for convenient statistics. The emotional bias information is supportive, objectionable, or neutral. Wherein, support indicates that the node agrees with the network event, and deprecate indicates that the node disagrees with the network event.
Step S108, if the emotional bias information is supporting or resisting, the network event is propagated to the adjacent nodes.
The emotional bias information is that the nodes supporting or resisting have strong propagation willingness to the network event. The network event may be propagated from the current node to each of the next adjacent nodes. If the current node supports or opposes the emotional bias information of the network event, the current node is strong in willingness of propagating the network event, and the current node is willing to propagate the network event.
And step S110, if the emotional bias information is neutral, finishing the propagation of the network event at the current node.
Nodes whose emotional bias information is neutral do not have any intention to propagate network events. The network event arriving at the neutral node stops propagating to the next node.
The embodiment of the invention provides a simulation method for network event propagation, which is characterized in that after a current node acquires a network event, the method acquires the attribute of the network event and the node attribute of the current node, calculates the emotional attitude information of the current node to the network event according to the attribute of the network event and the node attribute and the historical emotional attitude information of the previous node, and obtains the emotional deviation information of the current node by calculating the emotional attitude information: supporting, resisting or neutralizing, if the emotional bias information is resisting or supporting, continuing to propagate the network event, and if the emotional bias information is neutralizing, stopping the propagation of the network event at the current node. The embodiment of the invention improves the accuracy of information transmission process simulation by adding the calculation of the emotional attitude information, and is more suitable for practical application.
In order to screen the network event, obtain the node attribute of the current node, and before the step of calculating the emotional attitude information of the current node according to the historical emotional attitude information of the previous node, the attribute of the network event and the node attribute, the method further comprises: judging whether the current node is in an immune area of the network event or not according to the attribute of the network event and the attribute of the node, wherein the node in the immune area can shield the network event; and if not, calculating the emotional attitude information.
The immune area is used for screening network events and comprises a plurality of nodes capable of shielding external event input. Judging whether the current node is in the range of the immune area of the current type of network event according to the attributes of the event and the attributes of the node, if so, shielding the type of network event by the current node, namely stopping the propagation of the network event at the current node; if not, the current node does not shield the network event of the type, the network event can be continuously propagated at the current node, and the emotional attitude information of the current node to the network event is calculated.
In view of improving the efficiency of the network event and the network event attribute, the step of obtaining the network event and the network event attribute comprises:
(1) a network event is obtained.
If the current node is the source node, the network event is obtained from the network, referring to the activation derivative point table shown in tables 1-5, and the network event includes attributes such as an event id, an event origin point and time corresponding to the origin point. And if the current node is not the source node, acquiring the network event from the previous node, and acquiring the emotional attitude information of the previous node on the network event while acquiring the network event from the previous node.
Tables 1-5 activation derived points table
(2) Attributes of the network event are matched for the current node in an event attribute database.
Referring to the event attribute information table shown in table 1-1, which is an example of an event attribute information table in the event attribute database, for a network event of a current node, its attributes including a propagation time unit, a time type, a time subject, and the like are matched in the event attribute information table.
TABLE 1-1 event Attribute information Table
In order to obtain the emotional attitude information of the current node to the network event, the emotional attitude information may be calculated. Therefore, the step of obtaining the node attribute of the current node and calculating the emotional attitude information of the current node according to the historical emotional attitude information of the previous node, the attribute of the network event and the node attribute comprises the following steps:
(1) matching node attributes for the current node in a node attribute database, the node attributes at least comprising: node identification, node immunity, node dissemination and topic sensitivity.
See the network topology node attribute information table shown in tables 1-2, which is an example of data in the node attribute database. And matching the node attributes for the current node according to the network topology node attribute information table.
Table 1-2 network topology node attribute information table
(2) And determining the topic sensitivity of the current node to the network event according to the node attribute and the attribute of the network event.
Topic sensitivity is used to describe the attention of the current node to different network information. According to the attribute of the network event, the topic sensitivity of the current node to the network event can be obtained from the node attribute database.
(3) Acquiring historical emotional attitude information of a previous node; and calculating the emotional attitude information of the current node according to the historical emotional attitude information and the theme sensitivity.
The historical emotional attitude information of the previous node has a certain influence on the emotional attitude information of the current node. The network event is transmitted from the previous node to the current node, and the emotional attitude information of the current node is 0.5+ the topic sensitivity of the node is 0.5. The topic sensitivity corresponds to the corresponding sendivityid in tables 1-2, and the specific numerical distribution is shown in the topic sensitivity tables 1-4.
Table 1-4 topic sensitivity tables
For convenience of statistics, the nodes can be classified according to the emotional attitude information. The method for determining the emotional bias information of the current node to the network event according to the emotional attitude information comprises the following steps: segmenting the value of the emotional attitude information to obtain a segmentation result; and determining the emotional deviation information of the current node to the network event according to the segmentation result.
Referring to the topic sensitivity table shown in tables 1 to 4, the value of the emotional attitude information is obtained through the summary table and is segmented according to the value of the emotional attitude information, for example: segmenting and determining the emotional deviation information according to the value of the emotional attitude information as follows: a supporter (the 5), a neutralizer (-5< ═ the 5) and an objector (the-5), and updates the topic sensitivity table (the value is greater than 10, the value is 10, and the value is less than-10, the value is-10).
In order to better conform to the actual situation of network event propagation, in actual propagation, supported or opposed propagators usually have stronger propagation willingness. Thus, if the emotional bias information is supporting or opposing, the step of propagating the network event to the neighboring node comprises: acquiring the propagation probability of a network event between a current node and a next node; and propagating the network event to the adjacent nodes according to the propagation probability.
Referring to the network topology edge information tables shown in tables 1 to 3, when the current node supports or reverses the emotional bias information of the network event, the propagation probability between two nodes can be queried in the data recorded in the tables, and the network event can be propagated to the adjacent nodes according to the propagation probability.
Table 1-3 network topology edge information table
In order to understand the possible propagation result of the network event and decide whether to take proper supervision and intervention measures in advance, the method further comprises the following steps: respectively calculating emotional attitude information of all nodes in the network, and determining emotional deviation information of all nodes to the network event according to the emotional attitude information; and generating the overall emotion deviation distribution information of the network according to the emotion deviation information of all the nodes.
Traversing all nodes in the network, respectively calculating emotional attitude information and emotional deviation information, when a network event is transmitted among the nodes, the emotional attitude information of the transmitted nodes can influence the current node, respectively recording and timely updating the emotional attitude information and the emotional deviation information of each node, after traversing all the nodes, obtaining the emotional deviation information of all the nodes, thereby obtaining the emotional deviation distribution information of the network population, and performing statistical analysis on the attitude information of each node in the network event according to the emotional deviation distribution information of the network population so as to take necessary measures in time.
For example, suppose that a piece of information is currently on the microblog and a small number of X (X is an account set) people forward the rumor, we need to predict whether the rumor will cause the consequence of flooding so as to decide whether to take appropriate supervision and intervention measures in advance. First, we need to prepare in advance various databases of microblog user accounts and their mutual attention relationships, as shown in the provided data tables. Then we need to use the current propagation state of rumors as the input state of the deduction model, that is, the forwarded x account numbers are input into the network as the initial activated nodes, and then through the iterative deduction of the method shown in the present invention, the flooding condition of rumors after several time steps is obtained, so as to give the suggestion of decision support: if after some time the derived results show rumor flooding and the negative emotions are more severe, the decision maker is advised to take intervention in advance.
Referring to a data flow diagram of a simulation method for network event propagation shown in fig. 2, in the simulation method, the simulation device and the simulation equipment for network event propagation provided by the embodiment of the present invention, node emotional attitude information calculation is introduced through an event attribute database and a node attribute database, so as to obtain emotional deviation information, and network event propagation or propagation completion is controlled according to the type of the emotional deviation information and a network topology database, so that the deduction is closer to the reaction of a real person to a network event; by introducing judgment of the immune area, the firewall function in actual network filtering can be met.
Example 2
Embodiment 2 of the present invention provides a simulation apparatus for network event propagation, which is described in a block diagram of a structure of the simulation apparatus for network event propagation shown in fig. 3, and includes:
an event acquiring module 31, configured to acquire a network event and an attribute of the network event; the attributes include at least one of: time, type, or subject; the calculation module 32 is used for acquiring the node attribute of the current node and calculating the emotional attitude information of the current node according to the historical emotional attitude information of the previous node, the attribute of the network event and the node attribute; the emotion deviation module 33 is used for determining emotion deviation information of the current node to the network event according to the emotion attitude information; the emotional bias information is any one of the following: supportive, anti-or neutral; a control module 34 for propagating the network event to the neighboring node if the emotional bias information is supporting or opposing; the control module 34 is further configured to end the propagation of the network event at the current node if the emotional bias information is neutral.
Referring to another block diagram of the simulation apparatus for network event propagation shown in fig. 4, the apparatus further includes an immune region determining module 35, configured to: judging whether the network event belongs to an immune region or not according to the attribute of the network event, wherein nodes in the immune region can shield the network event; and if not, calculating the emotional attitude information.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The implementation principle and the generated technical effect of the simulation device for network event propagation provided by the embodiment of the present invention are the same as those of the simulation method for network event propagation described above, and for a brief description, reference may be made to the corresponding content in the simulation method for network event propagation described above, where the embodiment of the simulation device for network event propagation is not mentioned in part.
Example 3
Embodiment 3 of the present invention provides an electronic device, referring to a schematic block diagram of a structure of the electronic device shown in fig. 5, the electronic device includes a memory 41 and a processor 42, the memory stores a computer program operable on the processor, and the processor executes the computer program to implement the steps of any one of the simulation method embodiments of network event propagation.
The memory 41 is used for storing a program, and the processor 42 executes the program after receiving an execution instruction, and the method executed by the apparatus defined by the flow process disclosed in any of the foregoing embodiments of the present invention may be applied to the processor 42, or implemented by the processor 42.
The processor 42 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by instructions in the form of hardware, integrated logic circuits, or software in the processor 42. The Processor 42 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory 41, and a processor 42 reads information in the memory 41 and performs the steps of the method in combination with hardware thereof.
The electronic device provided by the embodiment of the invention has the same technical characteristics as the simulation method for network event propagation provided by the embodiment, so that the same technical problems can be solved, and the same technical effects can be achieved.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. A method for simulating network event propagation, comprising:
acquiring a network event and the attribute of the network event; the attributes include at least one of: time, type, or subject; the types include at least one of: rumors, terrorism, or group activities; the types are obtained by dividing according to the content of the network event;
acquiring the node attribute of a current node, and calculating the emotional attitude information of the current node according to the historical emotional attitude information of the previous node, the attribute of the network event and the node attribute; the node attributes include at least: node identification, node immunity, node propagation and topic sensitivity;
determining emotion deviation information of the current node to the network event according to the emotion attitude information; the emotional bias information is any one of the following information: supportive, anti-or neutral;
propagating the network event to a neighboring node if the emotional bias information is supportive or objectionable;
if the emotional deviation information is neutral, finishing the propagation of the network event at the current node;
the step of determining the emotion deviation information of the current node to the network event according to the emotion attitude information comprises the following steps:
segmenting the value of the emotional attitude information to obtain a segmentation result;
determining the emotional deviation information of the current node to the network event according to the segmentation result;
the step of obtaining the node attribute of the current node and calculating the emotional attitude information of the current node according to the historical emotional attitude information of the previous node, the attribute of the network event and the node attribute comprises the following steps:
matching node attributes for the current node in a node attribute database;
determining the topic sensitivity of the current node to the network event according to the node attribute and the attribute of the network event;
acquiring historical emotional attitude information of a previous node;
and calculating the emotional attitude information of the current node according to the historical emotional attitude information and the theme sensitivity.
2. The method according to claim 1, wherein before the step of obtaining the node attribute of the current node and calculating the emotional attitude information of the current node according to the historical emotional attitude information of the previous node, the attribute of the network event and the node attribute, the method further comprises:
judging whether the current node is in an immune area of the network event or not according to the attribute of the network event and the attribute of the node, wherein the node in the immune area can shield the network event;
and if not, calculating the emotional attitude information.
3. The method of claim 1, wherein the step of obtaining the network event and the attributes of the network event comprises:
acquiring a network event;
attributes of the network event are matched for the current node in an event attribute database.
4. The method of simulating propagation of a network event according to claim 1, wherein the step of propagating the network event to a neighboring node if the emotional bias information is supporting or opposing comprises:
acquiring the propagation probability of a network event between a current node and a next node;
and propagating the network event to the adjacent nodes according to the propagation probability.
5. The method of simulating propagation of a network event according to any of claims 1-4, wherein the method further comprises:
respectively calculating the emotional attitude information for all nodes in the network, and determining the emotional deviation information of all nodes to the network event according to the emotional attitude information;
and generating overall network emotion deviation distribution information according to the emotion deviation information of all the nodes.
6. An apparatus for simulating propagation of network events, comprising:
the event acquisition module is used for acquiring a network event and the attribute of the network event; the attributes include at least one of: time, type, or subject; the types include at least one of: rumors, terrorism, or group activities; the types are obtained by dividing according to the content of the network event;
the computing module is used for acquiring the node attribute of the current node and computing the emotional attitude information of the current node according to the historical emotional attitude information of the previous node, the attribute of the network event and the node attribute; the node attributes include at least: node identification, node immunity, node propagation and topic sensitivity;
the emotion deviation module is used for determining emotion deviation information of the current node on the network event according to the emotion attitude information; the emotional bias information is any one of the following information: supportive, anti-or neutral;
a control module for propagating the network event to a neighboring node if the emotional bias information is supporting or opposing;
the control module is further used for ending the propagation of the network event at the current node if the emotional bias information is neutral;
the emotion bias module is further configured to:
segmenting the value of the emotional attitude information to obtain a segmentation result;
determining the emotional deviation information of the current node to the network event according to the segmentation result;
the computing module is further configured to:
the step of obtaining the node attribute of the current node and calculating the emotional attitude information of the current node according to the historical emotional attitude information of the previous node, the attribute of the network event and the node attribute comprises the following steps:
matching node attributes for the current node in a node attribute database;
determining the topic sensitivity of the current node to the network event according to the node attribute and the attribute of the network event;
acquiring historical emotional attitude information of a previous node;
and calculating the emotional attitude information of the current node according to the historical emotional attitude information and the theme sensitivity.
7. The simulation apparatus of network event propagation according to claim 6, wherein the apparatus further comprises an immune region determination module configured to:
judging whether the current node is in an immune area of the network event or not according to the attribute of the network event and the attribute of the node, wherein the node in the immune area can shield the network event;
and if not, calculating the emotional attitude information.
8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program operable on the processor, and wherein the processor implements the steps of the method of any of claims 1 to 5 when executing the computer program.
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