CN114786044A - Management method and device of live broadcast platform, computer equipment and storage medium - Google Patents

Management method and device of live broadcast platform, computer equipment and storage medium Download PDF

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Publication number
CN114786044A
CN114786044A CN202210367615.2A CN202210367615A CN114786044A CN 114786044 A CN114786044 A CN 114786044A CN 202210367615 A CN202210367615 A CN 202210367615A CN 114786044 A CN114786044 A CN 114786044A
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Prior art keywords
users
class
violation
user
illegal
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CN202210367615.2A
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Chinese (zh)
Inventor
叶镇亮
白银硕
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Guangzhou Boguan Information Technology Co Ltd
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Guangzhou Boguan Information Technology Co Ltd
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Priority to CN202210367615.2A priority Critical patent/CN114786044A/en
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/25—Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication, learning user preferences for recommending movies
    • H04N21/258—Client or end-user data management, e.g. managing client capabilities, user preferences or demographics, processing of multiple end-users preferences to derive collaborative data
    • H04N21/25866—Management of end-user data
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
    • H04N21/4508—Management of client data or end-user data
    • H04N21/4532—Management of client data or end-user data involving end-user characteristics, e.g. viewer profile, preferences
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/47—End-user applications
    • H04N21/475—End-user interface for inputting end-user data, e.g. personal identification number [PIN], preference data
    • H04N21/4751—End-user interface for inputting end-user data, e.g. personal identification number [PIN], preference data for defining user accounts, e.g. accounts for children
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/47—End-user applications
    • H04N21/478—Supplemental services, e.g. displaying phone caller identification, shopping application
    • H04N21/4788—Supplemental services, e.g. displaying phone caller identification, shopping application communicating with other users, e.g. chatting

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  • Engineering & Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • General Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Child & Adolescent Psychology (AREA)
  • General Health & Medical Sciences (AREA)
  • Human Computer Interaction (AREA)
  • Computer Graphics (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The embodiment of the application discloses a management method and device of a live broadcast platform, computer equipment and a storage medium. According to the scheme, first-class users with illegal behaviors are counted according to historical illegal data recorded by a live broadcast platform, second-class users with higher relevance with the first-class users are screened out from the users of the live broadcast platform, illegal risk users are obtained according to other first-class users with higher relevance with the second-class users, then illegal detection is carried out on the illegal risk users, target illegal users are determined, the target illegal users are provided for the illegal users who control the live broadcast platform in advance, therefore, the illegal users can be managed in advance, and the management efficiency of the live broadcast platform is improved.

Description

Management method and device of live broadcast platform, computer equipment and storage medium
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for managing a live broadcast platform, a computer device, and a storage medium.
Background
With the development of internet and network video live broadcast technologies, more and more people join the industry of anchor, in order to attract more audiences to watch, some anchor play illegal contents in the live broadcast room, and the live broadcast platform needs to manage and control the illegal live broadcast room.
In the related technology, the live broadcast platform mainly detects and screens illegal contents of contents published by each user, finds the illegal users through detection results, and then carries out related punishment on the illegal users, but the number of contents published by the users of the live broadcast platform is large, and the illegal contents need to be detected and screened by spending more time, so that the control of the illegal users is delayed.
Disclosure of Invention
The embodiment of the application provides a management method and device for a live broadcast platform, a computer device and a storage medium, which can improve the user control efficiency of the live broadcast platform.
The embodiment of the application provides a management method of a live broadcast platform, which comprises the following steps:
determining first-class illegal users with historical illegal behaviors in first-class users of a live broadcast platform, wherein the first-class users are one of anchor users or audience users;
acquiring a second class of users who have interacted with the first class of illegal users in the live broadcast platform, wherein the second class of users are the other one of the anchor users or the audience users;
and predicting to obtain a first class of violation risk users based on a first class of users who interact with the second class of users on the live broadcast platform.
Correspondingly, the embodiment of the present application further provides a management device for a live broadcast platform, including:
the device comprises a first determining unit, a second determining unit and a third determining unit, wherein the first determining unit is used for determining first-class illegal users with historical illegal behaviors in first-class users of a live broadcast platform, and the first-class illegal users are one of anchor users or audience users;
an obtaining unit, configured to obtain a second class of users who have interacted with the first class of illegal users in the live broadcast platform, where the second class of users is the other of the anchor user or the audience user;
and the prediction unit is used for predicting to obtain a first class of violation risk users based on the first class of users who have interacted with the second class of users on the live broadcast platform.
In some embodiments, the prediction unit comprises:
the first acquisition subunit is used for acquiring historical interaction information of the second class of users and the first class of users;
and the first determining subunit is used for determining the first class of violation risk users from the first class of users according to the historical interaction information.
In some embodiments, the first determining subunit is specifically configured to:
determining, from the historical interaction information, a gift amount that the audience user gifts a gift to each anchor user;
and obtaining the first class of violation risk users based on the anchor users who receive the gifts given by the audience users and have the gift number larger than the preset number.
In some embodiments, the first determining subunit is specifically configured to:
determining from the historical interaction information, a gift amount that each audience user presents a gift that the anchor user received;
and obtaining the first class of violation risk users based on audience users whose gift number for gifting the main broadcast user is greater than a preset number.
In some embodiments, the apparatus further comprises:
and the first detection unit is used for carrying out violation detection on the account data of the first class of violation risk users and determining a target first class of violation users in the first class of violation risk users.
In some embodiments, the first detection unit comprises:
the second obtaining subunit is configured to obtain historical user data generated by the first type of violation risk user at the user account associated with the live broadcast platform;
and the second determining subunit is used for obtaining the target first-class violation users based on the first-class violation risk users with violation data in the historical user data.
In some embodiments, the first detection unit further comprises:
the calculating subunit is used for calculating the violation risk degree of the first type of violation risk users according to the historical user data;
and the third determining subunit is used for obtaining the target first-class violation users based on the first-class violation risk users with violation risk degrees larger than the preset violation risk degrees.
In some embodiments, the obtaining unit comprises:
the third acquisition subunit is used for acquiring a second class of candidate users which interact with the first class of illegal users in the live broadcast platform;
and the fourth determining subunit is used for determining the second class of users from the second class of candidate users according to the historical interaction frequency of the second class of candidate users and the first class of illegal users.
In some embodiments, the apparatus further comprises:
and the second detection unit is used for carrying out violation detection on the account data of the second class of users and determining a target second class violation user in the second class of users.
In some embodiments, the apparatus further comprises:
the second determining unit is used for determining the violation level of the target first-class violation users according to the violation information of the target first-class violation users;
and the management unit is used for managing the target first-class violation users based on the violation management information corresponding to the violation levels.
Correspondingly, an embodiment of the present application further provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the management method for the live broadcast platform provided in any one of the embodiments of the present application.
Correspondingly, the embodiment of the application further provides a storage medium, wherein a plurality of instructions are stored in the storage medium, and the instructions are suitable for being loaded by a processor so as to execute the management method of the live broadcast platform.
According to the method and the device, the first class users with illegal behaviors are counted according to historical illegal data recorded by a live broadcast platform, the second class users with higher relevance with the first class users are screened out from the users of the live broadcast platform, the illegal risk users are obtained according to the prediction of other first class users with higher relevance with the second class users, further illegal detection is carried out on the illegal risk users, target illegal users are determined, the target illegal users are provided for the illegal users who are managed and controlled in advance on the live broadcast platform, therefore, the illegal users can be managed in advance, and the management efficiency of the live broadcast platform is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flowchart of a management method for a live broadcast platform according to an embodiment of the present application.
Fig. 2 is a schematic flowchart of another management method for a live broadcast platform according to an embodiment of the present application.
Fig. 3 is a block diagram of a management apparatus of a live broadcast platform according to an embodiment of the present application.
Fig. 4 is a schematic structural diagram of a computer device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. 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 application.
The embodiment of the application provides a method and a device for managing a live broadcast platform, a storage medium and computer equipment. Specifically, the management method of the live broadcast platform in the embodiment of the present application may be executed by a computer device, where the computer device may be a server or other devices. The server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing basic cloud computing services such as cloud service, a cloud database, cloud computing, a cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, CDN, and a big data and artificial intelligence platform.
For example, the computer device may be a server that may determine that a first type of offending user with historical offending behavior exists among first type users of a live platform, wherein the first type of offending user is one of a main broadcasting user or a spectator user; acquiring a second class of users who have interacted with a first class of illegal users in a live broadcast platform, wherein the second class of users are the other one of the anchor users or audience users; predicting to obtain a first class of violation risk users based on a first class of users who have interacted with a second class of users on a live broadcast platform; and carrying out violation detection on account data of the first class of violation risk users, and determining target first class violation users in the first class of violation risk users.
Based on the foregoing problems, embodiments of the present application provide a method and an apparatus for managing a live broadcast platform, a computer device, and a storage medium, which can improve user management and control efficiency of the live broadcast platform.
The following are detailed below. It should be noted that the following description of the embodiments is not intended to limit the preferred order of the embodiments.
The embodiment of the application provides a management method for a live broadcast platform, which can be executed by a terminal or a server.
Referring to fig. 1, fig. 1 is a schematic flowchart illustrating a management method of a live broadcast platform according to an embodiment of the present disclosure. The specific process of the management method of the live broadcast platform can be as follows:
101. and determining the first type of illegal users with historical illegal behaviors in the first type of users of the live broadcast platform.
In the embodiment of the application, the live broadcast platform refers to a platform for live broadcast of a user, the live broadcast platform can be a live broadcast application or a live broadcast website, the user can register on the live broadcast platform by utilizing personal information, and the live broadcast can be performed by logging in the live broadcast platform after the registration is successful. The live platform may include different types of users, for example, the live platform may include a host user, a viewer user, and the like. The anchor user refers to a user who performs live broadcasting, and the viewer user refers to a user who watches live broadcasting.
Wherein the first type of user may be one of a anchor user or a viewer user.
The historical violation refers to historical time, that is, the violation before the current time, the violation refers to a violation that the user makes a rule violation on the live broadcast platform, and the violation may include violation language, violation action, and the like. The first type of illegal user refers to a user who has made an illegal action before the current time in the first type of user.
For example, a first category of users may be anchor users, and the live platform may include: and when detecting that the anchor user A generates violation behaviors at the historical moment, the anchor user A can be determined to be a first-class violation user.
In some embodiments, to improve the detection accuracy of the offending user, the step "determining that there is an offending user with historical violations among users in the first category of the live platform" may include the following operations:
acquiring historical violation data of a live broadcast platform;
and determining the first type of violation users from the first type of users according to historical violation data.
The historical violation data comprise violation contents existing in the live broadcast platform before the current moment, violation users are further determined according to the violation contents, and then the first class of users are screened out from the violation users, so that the first class of violation users is obtained.
In some embodiments, to improve the efficiency of detecting the offending users, the step of "determining the offending users in the first category of users of the live platform that have historical offending behaviors" may include the following operations:
acquiring user tag information corresponding to a first type of user in a live broadcast platform;
and determining the first type of illegal users from the first type of users according to the user tag information.
Specifically, after the live broadcast platform detects the illegal user, the illegal user may be marked, for example, the user a detects that an illegal action exists in the live broadcast platform, and may mark the user a as the illegal user, and store the mark in the tag information of the user a. That is, the user tag information includes whether the user is an offending user.
Specifically, user tag information of all first-class users is obtained, and the first-class users with violation behavior marks in the user tag information are used as first-class violation users.
102. And acquiring a second class of users who interact with the first class of illegal users in the live broadcast platform.
In the embodiment of the application, the interaction between users in the live broadcast platform can include various modes, such as modes of generating interaction behaviors among various users, such as attention, gift, praise, chat, comment, live broadcast interaction and the like.
Wherein the second type of user is the other of the anchor user or the audience user. For example, the first type of user may be a main broadcasting user, and the second type of user may be a viewer user; alternatively, the first type of user may be a viewer user and the second type of user may be a anchor user.
In some embodiments, since the number of users of the live platform is large and there are many interactive users, in order to improve detection efficiency for illegal users, the step "acquiring a second class of users who have interacted with a first class of illegal users in the live platform" may include the following operations:
acquiring a second type of candidate users which interact with the first type of illegal users in the live broadcast platform;
and determining a second class of users from the second class of candidate users according to the historical interaction frequency of the second class of candidate users and the first class of illegal users.
And the second type of candidate users are users except the first type of users in the live broadcast platform.
Specifically, all users who interact with the first-class illegal user are screened out from the live broadcast platform, and then users except the first-class illegal user are further screened out from the users to obtain a second-class candidate user.
For example, a first type of offending user may be user a, and users in the live platform may include: user a, user B, user C, user D, user E, etc. The user a, the user D, and the user E may be users of the first category. Then, screening out users who have interacted with the user a from the users in the live platform, which may include: the user B, the user C, and the user D then screen out users other than the first type of user, that is, the second type of candidate user, from the users who have interacted with the user a, which may be: user B, user C.
The historical interaction frequency refers to the frequency of interaction between users of the live broadcast platform before the current moment. The historical interaction frequency can be calculated according to the previous interaction type of the user, the interaction times and the like. The interaction type, namely the interaction mode, comprises: concern, gift, like, chat, comment, live interaction, etc.
Specifically, the second class of users is determined from the second class of candidate users according to the historical interaction frequency of the second class of candidate users and the first class of illegal users, which may be determined from the second class of candidate users that the historical interaction frequency with the first class of illegal users is greater than the preset interaction frequency, and the determined second class of users is taken as the second class of users.
For example, a first type of offending user may be: user a, the second category of candidate users may be: the user B and the user C, calculating the historical interaction frequency of the user a and the user B may be: the first frequency, which is calculated as the historical interaction frequency of the user a and the user C, may be: a second frequency, wherein if the first frequency is greater than the preset interaction frequency, the user B can be determined as a second user; if the second frequency is greater than the preset interaction frequency, it can be determined that the user C is the second user.
In some embodiments, if the second type of users are users who frequently interact with the first type of illegal users, the second type of users have a high violation risk, and in order to enhance the user control of the live broadcast platform, after the step "determining the second type of users from the second type of candidate users according to the historical interaction frequency of the second type of candidate users with the first type of illegal users", the following steps may be further included:
and carrying out violation detection on the account data of the second class of users, and determining target second class violation users in the second class of users.
The account data of the second type of user refers to user data corresponding to a user account number associated with the second type of user on the live broadcast platform, and the account data may include all account information of the second type of user on the live broadcast platform, for example, the account data includes personal information, behavior information on the live broadcast platform, and the like, where the behavior information may include chat content, content published through the live broadcast platform, interactive content with other users, and the like.
Specifically, the violation detection of the account data of the second type of user may include detecting behavior information of the second type of user on the live broadcast platform, determining whether a violation really exists, and obtaining the second type of violation user based on the second type of user who really exists the violation.
For example, a second class of users may include: the user B and the user C respectively detect the account data of the user B and the user C, and if the account data of the user B is detected to have violation behaviors, the user B can be determined to be a second class of violation users; if the account data of the user C is detected to have the illegal behaviors, the user C can be determined to be a second class of illegal users. And then managing the target second-class violation users, and carrying out violation reminding or corresponding punishing.
103. And predicting to obtain the first class of violation risk users based on the first class of users who interact with the second class of users on the live broadcast platform.
In the embodiment of the application, after the second class of users with higher interactivity with the first class of illegal users is determined, the first class of users with violation risks can be predicted in a collaborative filtering mode according to other first class of users with higher interactivity with the second class of users in the live broadcast platform, so that the detection efficiency of the illegal users can be improved.
The first-class violation risk users refer to the first-class users with higher violation risk.
In some embodiments, in order to screen out a first type of users with higher violation risk, the step "predicting a first type of violation risk users based on the first type of users who have interacted with a second type of users on a live broadcast platform" may include the following operations:
acquiring historical interaction information of a second class of users and a first class of users;
and determining first-class violation risk users from the first-class users according to historical interaction information.
The historical interaction information refers to all interaction information of the second type of users and the first type of users interacting on the live broadcast platform before the current moment, and includes but is not limited to attention, gifts, praise, chatting, comments, live broadcast interaction and the like. And then, screening out the first class users with higher interaction degree, namely the first class users with higher association degree from the first class users interacting with the second class users according to the historical interaction information to obtain the first class of violation risk users.
In some embodiments, the first type of user may be an anchor user, the second type of user may be an audience user, and the step "determining a first type of violation risk user from the first type of user according to the historical interaction information" may include the following operations:
determining the gift number of gifts given to each anchor user by audience users from historical interaction information;
and obtaining first-class violation risk users based on the anchor users who receive the gifts given by the audience users and have the gift number larger than the preset number.
Specifically, in order to ensure that the screened first class of violation risk users are users with higher violation risk, that is, to improve the accuracy of predicting the violation users, users with higher association with the second class of users may be selected from the first class of users who have interacted with the second class of users, and the selected users are used as the first class of violation risk users.
The historical interactive information comprises gift giving information among the live platform users. The user having a higher degree of association may be determined based on gift-giving information between users.
When the first type of users are anchor users and the second type of users are audience users, the first type of illegal users refer to illegal anchor users, and the first type of illegal risk users refer to illegal risk anchor users.
Further, determining the gift number of the audience users for gift donation to the anchor users except the illegal anchor user in the live broadcast platform from the historical interactive information, and screening the illegal risk anchor users from other anchor users according to the comparison result of the gift number and the preset number.
For example, the offending anchor user may be user a, and the audience users with a higher degree of interaction with user a may be: user B, other anchor users may include: the user C, the user D and the like, the obtaining of the historical interaction information may be obtaining gift-giving information of the user B to the user C and gift-giving information of the user B to the user D. For example, the gift amount given by the user B to the user C may be: the first amount, the number of gifts gifted by the user B to the user D, may be: and the second quantity, namely the first quantity and the second quantity can be respectively compared with the preset quantity, and the anchor users corresponding to the gift-giving information of which the quantity is greater than the preset quantity are determined as violation risk anchor users, namely first violation risk users. The interactive relevance between the users is determined through the gift sending quantity, so that the prediction accuracy of the illegal users can be improved.
In some embodiments, the first type of user may be a spectator user, the second type of user may be an anchor user, and the step "determining a first type of violation risk user from the first type of user according to historical interaction information" may include the following operations:
determining the gift quantity of each audience user gifted gift received by the anchor user from the historical interaction information;
based on audience users whose gift number for presenting gifts to the anchor user is larger than the preset number, a first class of violation risk users is obtained.
When the first type of users are audience users and the second type of users are anchor users, the first type of illegal users refer to illegal audience users, and the first type of illegal risk users refer to illegal risk audience users.
Further, the method comprises the steps that the number of gifts given by other audience users of the live broadcast platform is received by the anchor user with higher interaction degree with the illegal audience users from historical interaction information, and the illegal risk audience users are screened out from the other audience users according to the comparison result of the number of the gifts and the preset number.
For example, the offending audience user may be user a, and the anchor user with a higher degree of interaction with user a may be: user B, other audience users may include: the user C, the user D and the like, the obtaining of the historical interaction information may be obtaining gift-giving information of the user C to the user B and obtaining gift-giving information of the user D to the user B. For example, the gift amount given by the user C to the user B may be: the third number, the number of gifts given by the user D to the user B, may be: and a fourth quantity, wherein the third quantity and the fourth quantity can be respectively compared with the preset quantity, and audience users corresponding to the gift-giving information of which the quantity is greater than the preset quantity are determined as violation risk audience users, namely first violation risk users.
In some embodiments, in addition to determining the degree of association between users from gift-giving information in the historical interaction information, the historical interaction information may further include: the association degree between the users can be determined according to the number of praise, the chat frequency and the like, and the greater the number of praise, the higher the association degree between the users is; the higher the chat frequency, the higher the correlation degree between users, and the like. This is not an example.
In some embodiments, to further regulate the detected violation account, the method may further include:
and carrying out violation detection on account data of the first class of violation risk users, and determining a target first class of violation users in the first class of violation risk users.
The method comprises the steps of carrying out violation detection on account data, namely detecting whether violation data exist in the account data or not. And judging the first class of illegal risk users of the account data with the illegal behavior data as target first class illegal users, namely the first class of users with the illegal behaviors, and further managing the users with the illegal behaviors.
In some embodiments, the step of "performing violation detection on account data of first-class violation risk users, and determining a target first-class violation user among the first-class violation risk users" may include the following operations:
acquiring historical user data generated by a user account number associated with a first type of violation risk user on a live broadcast platform;
and obtaining a target first-class violation user based on the first-class violation risk users with violation data in the historical user data.
In the embodiment of the application, a user of the live broadcast platform logs in by registering a user account and entering the live broadcast platform to perform live broadcast or watch live broadcast and other operations.
Specifically, after the user logs in the live platform, data corresponding to the operation of the user on the live platform is stored in the background and is associated with the user account of the user. When the first type of violation risk users are detected, historical user data generated by the first type of violation risk users in the user account associated with the live broadcast platform can be obtained, and the historical user data is all user data generated by the first type of violation risk users in the live broadcast platform before the current moment.
Furthermore, historical user data is detected, the historical user data can be matched with violation data, and the violation data can be violation behavior data predefined by a live broadcast platform. If the violation data exist in the historical user data of the first-class violation risk users, it can be determined that the first-class violation risk users have violation behaviors, and therefore the first-class violation risk users are the target first-class violation users.
In some embodiments, in order to avoid causing false detection of the illegal user, after the step of "obtaining historical user data generated by the first type of illegal risky user on a user account associated with the live broadcast platform", the following steps may be further included:
calculating the violation risk degree of the first type of violation risk users according to historical user data;
and obtaining a target first-class violation user based on the first-class violation risk users with violation risk degrees larger than the preset violation risk degree.
The violation risk degree refers to a risk index of the violation, and can be determined by the violation in the historical user data and the violation degree of the violation content by calculating the violation risk degree according to the historical user data.
Further, the target first-class violation users are determined from the first-class violation risk users according to the violation risk, and the target first-class violation users can be obtained according to the first-class violation risk users with the violation risk greater than the preset violation risk. By calculating the violation risk degree, the first-class violation risk users with higher violation risk degree are judged as the target first-class violation users, so that misdetection of other users without violation can be avoided, and the accuracy of violation user detection is improved.
In some embodiments, to implement the control of the illegal user of the live broadcast platform, the method may further include the following steps:
determining the violation level of the first-class target violation users according to the violation information of the first-class target violation users;
and managing the first-class target violation users based on violation management information corresponding to the violation levels.
The violation information of the target first-class violation users refers to the violation behaviors of the target first-class violation users on the live broadcast platform, and the violation level of the target first-class violation users is judged according to the violation behaviors. In the embodiment of the application, different violation management information is set according to different violation levels, so that different management is performed on users with different violation degrees, and the violation management efficiency is improved.
The violation management information may include punishment for violation of the user, where the lower the violation level is, the smaller the punishment is, for example, performing a reminder; the higher the violation level, the greater the penalty, such as blocking the user account.
The embodiment of the application discloses a management method of a live broadcast platform, which comprises the following steps: determining first-class illegal users with historical illegal behaviors in the first-class users of the live broadcast platform, wherein the first-class users are one of anchor users or audience users; acquiring a second class of users who have interacted with a first class of illegal users in a live broadcast platform, wherein the second class of users are the other one of the anchor users or audience users; and predicting to obtain the first class of violation risk users based on the first class of users who interact with the second class of users on the live broadcast platform. Therefore, the management efficiency of the live broadcast platform can be improved.
Based on the above description, the management method of the live platform of the present application will be further described below by way of example. Referring to fig. 2, fig. 2 is a schematic flow chart of another live broadcast platform management method according to an embodiment of the present application, and taking an example that the live broadcast platform management method is applied to a server, a specific flow may be as follows:
201. and the server acquires the illegal anchor users with illegal behaviors in the live broadcast platform before the current moment.
In this embodiment of the application, the server may mark the user who has the violation, for example, when it is detected that the user has the violation, the server generates violation marking information, and associates the violation marking information with account data of the user. So as to search the illegal user of the live platform in the following.
Specifically, the anchor user who has the violation behavior is obtained by screening the anchor user of the live broadcast platform, and then obtaining the violation anchor user according to the anchor user whose account data is associated with the violation marker information.
202. The server acquires audience users of which the interaction frequency with the illegal anchor users on the live broadcast platform meets preset conditions.
Wherein, interactive frequency refers to the frequency degree of carrying out the interaction between the user on the live platform, and wherein, interactive mode can include: concern, gift, like, chat, comment, live interaction, etc.
The interaction frequency meeting the preset condition can comprise that the interaction frequency is greater than the specified interaction frequency, and when the interaction frequency on the live broadcast platform between the users is greater than the specified interaction frequency, the higher the association degree between the users is, or the similar hobbies among the users can be represented.
For example, the violation anchor user may be: user a, the user in the live platform may further include: user B, user C, user D, and user E. The obtaining of the interaction frequencies of the user a and the user B may be: a first interaction frequency; the obtaining of the interaction frequency between the user a and the user C may be: a second interaction frequency; the obtaining of the interaction frequency between the user a and the user D may be: a third interaction frequency; the obtaining of the interaction frequency between the user a and the user E may be: and a fourth interaction frequency. And then comparing the interaction frequencies with the specified interaction frequencies respectively, and if the interaction frequency between the illegal anchor user and the user is greater than the specified interaction frequency, determining that the user is an audience user, for example, if the first interaction frequency is greater than the specified interaction frequency, determining that the user C is the screened audience user with higher association degree with the illegal anchor user.
203. The server screens anchor users with interaction frequency meeting preset conditions between the live platform and audience users from the anchor users of the live platform to obtain violation risk anchor users.
In this step, the screening method may be referred to by the anchor user who is screened from the anchor users and whose interaction frequency with the audience user meets the preset condition on the live broadcast platform, and is not described herein in detail. By the anchor users who interact with audience users and the interaction frequency meets the preset conditions, the anchor users with violation risks, namely the anchor users with violation risks, are predicted.
In some embodiments, when the rule violation risk anchor user is determined by the anchor user interacting with the audience user, the rule violation risk degree of the rule violation risk anchor user, that is, the rule violation risk score, may be calculated using a recommendation model for determining whether the rule violation risk anchor user belongs to the rule violation user.
204. And the server detects the violation behaviors of the violation risk anchor users and determines target violation anchor users in the violation risk anchor users.
Specifically, the violation detection is performed on the violation risk anchor user, that is, the account data of the violation risk anchor user is detected, and whether the violation data exists in the account data is judged. And judging the first class of illegal risk users of the account data with the illegal behavior data as target first class illegal users, namely the first class of users with the illegal behaviors, and further managing the users with the illegal behaviors.
The embodiment of the application discloses a management method of a live broadcast platform, which comprises the following steps: the server obtains illegal anchor users with illegal behaviors in the live broadcast platform before the current moment, obtains audience users with interaction frequency between the live broadcast platform and the illegal anchor users meeting preset conditions, screens the anchor users with interaction frequency between the live broadcast platform and the audience users meeting the preset conditions from the anchor users of the live broadcast platform to obtain illegal risk anchor users, detects the illegal behaviors of the illegal risk anchor users, and determines target illegal anchor users in the illegal risk anchor users. Each user of the live broadcast platform does not need to be detected one by one, violation risk users are predicted through the relevance between the users, the workload of manual violation behavior identification can be reduced, and the violation behavior detection efficiency is improved.
In order to better implement the management method for the live broadcast platform provided by the embodiment of the present application, the embodiment of the present application further provides a management device for the live broadcast platform based on the management method for the live broadcast platform. The meaning of the noun is the same as that in the management method of the live broadcast platform, and specific implementation details can refer to the description in the method embodiment.
Referring to fig. 3, fig. 3 is a block diagram of a management device of a live broadcast platform according to an embodiment of the present disclosure, where the management device includes:
a first determining unit 301, configured to determine a first class of illegal users with historical illegal behaviors among first class users of a live broadcast platform, where the first class of users are one of anchor users or audience users;
an obtaining unit 302, configured to obtain a second class of users who have interacted with the first class of illegal users in the live broadcast platform, where the second class of users is the other of the anchor user or the audience user;
the predicting unit 303 is configured to predict, based on a first class of users who have interacted with the second class of users on the live broadcast platform, a first class of violation risk users.
In some embodiments, the prediction unit 303 may include:
the first acquisition subunit is used for acquiring historical interaction information of the second class of users and the first class of users;
and the first determining subunit is used for determining the first class of violation risk users from the first class of users according to the historical interaction information.
In some embodiments, the first determining subunit may specifically be configured to:
determining from the historical interaction information a gift amount that the audience user gifts a gift to each of the anchor users;
and obtaining the first class of violation risk users based on the anchor users who receive the gifts given by the audience users and have the gift number larger than the preset number.
In some embodiments, the first determining subunit may be specifically configured to:
determining from the historical interaction information, a gift amount that each audience user presents a gift that the anchor user received;
and obtaining the first class of violation risk users based on audience users whose gift number for gifting the main broadcast user is greater than a preset number.
In some embodiments, the apparatus may further comprise:
and the first detection unit is used for carrying out violation detection on the account data of the first class of violation risk users and determining target first class violation users in the first class of violation risk users.
In some embodiments, the first detection unit may include:
the second obtaining subunit is configured to obtain historical user data generated by the first type of violation risk user at the user account associated with the live broadcast platform;
and the second determining subunit is used for obtaining the target first-class violation users based on the first-class violation risk users with violation data in the historical user data.
In some embodiments, the first detection unit may further include:
the calculating subunit is used for calculating the violation risk degree of the first type of violation risk users according to the historical user data;
and the third determining subunit is used for obtaining the target first-class illegal users based on the first-class illegal users with the illegal risk degrees larger than the preset illegal risk degrees.
In some embodiments, the obtaining unit 302 may include:
the third obtaining subunit is configured to obtain a second class of candidate users, who have interacted with the first class of illegal users, in the live broadcast platform;
and the fourth determining subunit is used for determining the second class of users from the second class of candidate users according to the historical interaction frequency of the second class of candidate users and the first class of illegal users.
In some embodiments, the apparatus may further comprise:
and the second detection unit is used for carrying out violation detection on the account data of the second class of users and determining a target second class violation user in the second class of users.
In some embodiments, the apparatus may further comprise:
the second determining unit is used for determining the violation level of the target first-class violation users according to the violation information of the target first-class violation users;
and the management unit is used for managing the target first-class violation users based on the violation management information corresponding to the violation levels.
The embodiment of the application discloses a management device of a live broadcast platform, which determines a first class of illegal users with historical violation behaviors in the first class of users of the live broadcast platform through a first determining unit 301, wherein the first class of users is one of an anchor user or an audience user, an obtaining unit 302 obtains a second class of users who have interacted with the first class of illegal users in the live broadcast platform, wherein the second class of users is the anchor user or the other one of the audience users, and a predicting unit 303 predicts the first class of illegal risk users based on the fact that the second class of users are in the first class of users who have interacted with the live broadcast platform. Therefore, the user control efficiency of the live broadcast platform can be improved.
Correspondingly, the embodiment of the application further provides a computer device, and the computer device can be a server. As shown in fig. 4, fig. 4 is a schematic structural diagram of a computer device according to an embodiment of the present application. The computer apparatus 400 includes a processor 401 having one or more processing cores, a memory 402 having one or more computer-readable storage media, and a computer program stored on the memory 402 and executable on the processor. The processor 401 is electrically connected to the memory 402. Those skilled in the art will appreciate that the computer device configurations illustrated in the figures are not meant to be limiting of computer devices and may include more or fewer components than those illustrated, or some components may be combined, or a different arrangement of components.
The processor 401 is a control center of the computer device 400, connects the respective parts of the entire computer device 400 using various interfaces and lines, performs various functions of the computer device 400 and processes data by running or loading software programs and/or modules stored in the memory 402 and calling data stored in the memory 402, thereby monitoring the computer device 400 as a whole.
In the embodiment of the present application, the processor 401 in the computer device 400 loads instructions corresponding to processes of one or more application programs into the memory 402 according to the following steps, and the processor 401 runs the application programs stored in the memory 402, thereby implementing various functions:
determining first-class illegal users with historical illegal behaviors in the first-class users of the live broadcast platform, wherein the first-class users are one of anchor users or audience users;
acquiring a second class of users who have interacted with a first class of illegal users in a live broadcast platform, wherein the second class of users are the other one of the anchor users or audience users;
and predicting to obtain a first class of violation risk users based on a first class of users who interact with a second class of users on the live broadcast platform.
In some embodiments, predicting the first class of violation risk users based on the first class of users who have interacted with the second class of users on the live broadcast platform may include:
acquiring historical interaction information of a second class of users and a first class of users;
and determining first class violation risk users from the first class of users according to the historical interaction information.
In some embodiments, the first type of users are anchor users and the second type of users are audience users;
determining a first class of violation risk users from the first class of users according to the historical interaction information may include:
determining the gift number of gifts given to each anchor user by audience users from historical interaction information;
and obtaining first-class violation risk users based on the anchor users who receive the gifts given by the audience users and have the gift number larger than the preset number.
In some embodiments, the first type of user is a spectator user and the second type of user is a anchor user;
determining a first class of violation risk users from the first class of users according to the historical interaction information may include:
determining the gift number of each audience user gifted gift received by the anchor user from the historical interaction information;
the first type of violation risk users are obtained based on audience users whose number of gifts given to the anchor user is greater than a preset number.
In some embodiments, further comprising:
and carrying out violation detection on account data of the first class of violation risk users, and determining target first class violation users in the first class of violation risk users.
In some embodiments, performing violation detection on account data of first-class violation risk users, and determining a target first-class violation user among the first-class violation risk users may include:
acquiring historical user data generated by a user account number associated with a first type of violation risk user on a live broadcast platform;
and obtaining a target first-class violation user based on the first-class violation risk users with violation data in the historical user data.
In some embodiments, after obtaining historical user data generated by a first type of violation risk user at a user account associated with a live platform, the method may further include:
calculating the violation risk degree of the first type of violation risk users according to historical user data;
and obtaining a target first-class violation user based on the first-class violation risk users with violation risk degrees larger than the preset violation risk degree.
In some embodiments, obtaining a second type of users who have interacted with a first type of illegal user in a live platform may include:
acquiring a second type of candidate users which interact with the first type of illegal users in the live broadcast platform;
and determining a second class of users from the second class of candidate users according to the historical interaction frequency of the second class of candidate users and the first class of illegal users.
In some embodiments, after determining a second type of user from the second type of candidate users according to the historical interaction frequency of the second type of candidate user with the first type of illegal user, the method may further include:
and carrying out violation detection on the account data of the second class of users, and determining target second class violation users in the second class of users.
In some embodiments, it may further include:
determining the violation level of the first-class target violation users according to the violation information of the first-class target violation users;
and managing the first-class target violation users based on violation management information corresponding to the violation levels.
According to the scheme, the first class users with illegal behaviors are counted according to historical illegal data recorded by the live broadcast platform, the second class users with higher relevance with the first class users are screened out from the users of the live broadcast platform, the illegal risk users are obtained according to other first class users with higher relevance with the second class users, then illegal detection is carried out on the illegal risk users, target illegal users are determined, the target illegal users are provided for the illegal users who control the live broadcast platform in advance, therefore, the illegal users can be managed in advance, and the management efficiency of the live broadcast platform is improved.
The above operations can be implemented in the foregoing embodiments, and are not described in detail herein.
Optionally, as shown in fig. 4, the computer device 400 further includes: a touch display 403, a radio frequency circuit 404, an audio circuit 405, an input unit 406, and a power supply 407. The processor 401 is electrically connected to the touch display 403, the rf circuit 404, the audio circuit 405, the input unit 406, and the power source 407 respectively. Those skilled in the art will appreciate that the computer device configuration illustrated in FIG. 4 does not constitute a limitation of computer devices, and may include more or fewer components than those illustrated, or some components may be combined, or a different arrangement of components.
The touch display screen 403 can be used for displaying a graphical user interface and receiving operation instructions generated by a user acting on the graphical user interface. The touch display screen 403 may include a display panel and a touch panel. The display panel may be used, among other things, to display messages entered by or provided to a user and various graphical user interfaces of the computer device, which may be composed of graphics, text, icons, video, and any combination thereof. Alternatively, the display panel may be configured in the form of a Liquid Crystal Display (LCD), an organic Light-Emitting Diode (OLED), or the like. The touch panel may be used to collect touch operations of a user on or near the touch panel (for example, operations of the user on or near the touch panel using any suitable object or accessory such as a finger, a stylus pen, and the like), and generate corresponding operation instructions, and the operation instructions execute corresponding programs. Alternatively, the touch panel may include two parts, a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives the touch message from the touch sensing device, converts it into touch point coordinates, and sends the touch point coordinates to the processor 401, and can receive and execute a command sent from the processor 401. The touch panel may overlay the display panel and, when the touch panel detects a touch operation thereon or nearby, transmit the touch operation to the processor 401 to determine the type of the touch event, and then the processor 401 provides a corresponding visual output on the display panel according to the type of the touch event. In the embodiment of the present application, the touch panel and the display panel may be integrated into the touch display screen 403 to realize input and output functions. However, in some embodiments, the touch panel and the touch panel can be implemented as two separate components to perform the input and output functions. That is, the touch display screen 403 may also be used as a part of the input unit 406 to implement an input function.
In the embodiment of the present application, a game application is executed by the processor 401 to generate a graphical user interface on the touch display screen 403, where a virtual scene on the graphical user interface includes at least one skill control area, and the skill control area includes at least one skill control. The touch display screen 403 is used for presenting a graphical user interface and receiving an operation instruction generated by a user acting on the graphical user interface.
The rf circuit 404 may be used for transceiving rf signals to establish wireless communication with a network device or other computer device through wireless communication, and to transmit and receive signals to and from the network device or other computer device.
The audio circuit 405 may be used to provide an audio interface between a user and a computer device through a speaker, microphone. The audio circuit 405 may transmit the electrical signal converted from the received audio data to a speaker, and convert the electrical signal into a sound signal for output; on the other hand, the microphone converts the collected sound signal into an electrical signal, which is received by the audio circuit 405 and converted into audio data, which is then processed by the audio data output processor 401, and then sent to, for example, another computer device via the radio frequency circuit 404, or output to the memory 402 for further processing. The audio circuit 405 may also include an earbud jack to provide communication of a peripheral headset with the computer device.
The input unit 406 may be used to receive input numbers, character messages, or user characteristic messages (e.g., fingerprints, irises, facial messages, etc.), and to generate keyboard, mouse, joystick, optical, or trackball signal inputs related to user settings and function control.
The power supply 407 is used to power the various components of the computer device 400. Optionally, the power supply 407 may be logically connected to the processor 401 through a power management system, so as to implement functions of managing charging, discharging, power consumption management, and the like through the power management system. The power supply 407 may also include any component of one or more dc or ac power sources, recharging systems, power failure detection circuitry, power converters or inverters, power status indicators, and the like.
Although not shown in fig. 4, the computer device 400 may further include a camera, a sensor, a wireless fidelity module, a bluetooth module, etc., which are not described in detail herein.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to the related descriptions of other embodiments.
As can be seen from the above, in the computer device provided in this embodiment, it is determined that there is a first type of illegal user with historical illegal behavior in the first type of users of the live broadcast platform, where the first type of user is one of an anchor user or a viewer user; acquiring a second class of users who interact with the first class of illegal users in the live broadcast platform, wherein the second class of users are the other one of the anchor users or the audience users; and predicting to obtain the first class of violation risk users based on the first class of users who interact with the second class of users on the live broadcast platform.
It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be performed by instructions, or by instructions controlling associated hardware, which may be stored in a computer-readable storage medium and loaded and executed by a processor.
To this end, an embodiment of the present application provides a computer-readable storage medium, in which a plurality of computer programs are stored, where the computer programs can be loaded by a processor to execute the steps in any method for managing a live broadcast platform provided in the embodiment of the present application. For example, the computer program may perform the steps of:
determining first-class illegal users with historical illegal behaviors in the first-class users of the live broadcast platform, wherein the first-class users are one of anchor users or audience users;
acquiring a second class of users who have interacted with a first class of illegal users in a live broadcast platform, wherein the second class of users are the other one of the anchor users or audience users;
and predicting to obtain a first class of violation risk users based on a first class of users who interact with a second class of users on the live broadcast platform.
In some embodiments, predicting the first class of violation risk users based on the first class of users who have interacted with the second class of users on the live broadcast platform may include:
acquiring historical interaction information of a second class of users and a first class of users;
and determining first class violation risk users from the first class of users according to the historical interaction information.
In some embodiments, the first type of users are anchor users and the second type of users are audience users;
determining a first class of violation risk users from the first class of users according to the historical interaction information may include:
determining the gift number of gifts given to each anchor user by audience users from historical interaction information;
and obtaining first-class violation risk users based on the anchor users who receive the gifts given by the audience users and have the gift number larger than the preset number.
In some embodiments, the first type of user is a spectator user and the second type of user is a anchor user;
determining a first class of violation risk users from the first class of users according to the historical interaction information may include:
determining the gift number of each audience user gifted gift received by the anchor user from the historical interaction information;
the first type of violation risk users are obtained based on audience users whose number of gifts given to the anchor user is greater than a preset number.
In some embodiments, further comprising:
and carrying out violation detection on account data of the first class of violation risk users, and determining target first class violation users in the first class of violation risk users.
In some embodiments, the violation detection of the account data of the first class of violation risk users and the determination of the target first class of violation users among the first class of violation risk users may include:
acquiring historical user data generated by a user account number associated with a first type of violation risk user on a live broadcast platform;
and obtaining a target first-class violation user based on the first-class violation risk users with violation data in the historical user data.
In some embodiments, after obtaining historical user data generated by a first type of violation risk user at a user account associated with a live platform, the method may further include:
calculating the violation risk degree of the first type of violation risk users according to historical user data;
and obtaining the target first-class violation users based on the first-class violation risk users with violation risk degrees larger than the preset violation risk degrees.
In some embodiments, obtaining a second type of users who have interacted with a first type of illegal user in a live platform may include:
acquiring a second type of candidate users which interact with a first type of illegal users in a live broadcast platform;
and determining a second class of users from the second class of candidate users according to the historical interaction frequency of the second class of candidate users and the first class of illegal users.
In some embodiments, after determining a second class of users from the second class of candidate users according to the historical interaction frequency of the second class of candidate users with the first class of illegal users, the method may further include:
and carrying out violation detection on the account data of the second class of users, and determining target second class violation users in the second class of users.
In some embodiments, it may further include:
determining the violation level of the first-class target violation users according to the violation information of the first-class target violation users;
and managing the first-class target violation users based on violation management information corresponding to the violation levels.
According to the scheme, the first class users with illegal behaviors are counted according to historical illegal data recorded by the live broadcast platform, the second class users with higher relevance with the first class users are screened out from the users of the live broadcast platform, the illegal risk users are obtained according to other first class users with higher relevance with the second class users, then illegal detection is carried out on the illegal risk users, target illegal users are determined, the target illegal users are provided for the illegal users who control the live broadcast platform in advance, therefore, the illegal users can be managed in advance, and the management efficiency of the live broadcast platform is improved.
The above operations can be implemented in the foregoing embodiments, and are not described in detail herein.
Wherein the storage medium may include: read Only Memory (ROM), random access Memory (RM), magnetic or optical disk, and the like.
Since the computer program stored in the storage medium can execute the steps in the management method for any live broadcast platform provided in the embodiment of the present application, beneficial effects that can be achieved by the management method for any live broadcast platform provided in the embodiment of the present application can be achieved, which are detailed in the foregoing embodiments and will not be described herein again.
The method, the apparatus, the storage medium, and the computer device for managing a live broadcast platform provided in the embodiments of the present application are described in detail above, and specific examples are applied in the present application to explain the principles and embodiments of the present application, and the description of the above embodiments is only used to help understand the method and the core idea of the present application; meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation manner and the application scope may be changed, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims (13)

1. A management method for a live broadcast platform is characterized by comprising the following steps:
determining first-class illegal users with historical illegal behaviors in first-class users of a live broadcast platform, wherein the first-class users are one of anchor users or audience users;
acquiring a second class of users who have interacted with the first class of illegal users in the live broadcast platform, wherein the second class of users are the other one of the anchor users or the audience users;
and predicting to obtain a first class of violation risk users based on the first class of users who have interacted with the second class of users on the live broadcast platform.
2. The method according to claim 1, wherein predicting a first class of violation risk users based on a first class of users who have interacted with a second class of users on the live broadcast platform comprises:
acquiring historical interaction information of the second class of users and the first class of users;
and determining the first class of violation risk users from the first class of users according to the historical interaction information.
3. The method of claim 2, wherein the first type of user is a anchor user and the second type of user is a viewer user;
the determining the first class of violation risk users from the first class of users according to the historical interaction information comprises:
determining from the historical interaction information a gift amount that the audience user gifts a gift to each of the anchor users;
and obtaining the first class of violation risk users based on the anchor users who receive the gifts given by the audience users and have the gift number larger than the preset number.
4. The method of claim 2, wherein the first type of user is a viewer user and the second type of user is a broadcaster user;
the determining the first class of violation risk users from the first class of users according to the historical interaction information includes:
determining, from the historical interaction information, a gift amount that the anchor user receives gifted gifts for each audience user;
and obtaining the first class of violation risk users based on audience users whose gift number for gifting the main broadcast user is greater than a preset number.
5. The method of claim 1, further comprising:
and carrying out violation detection on the account data of the first class of violation risk users, and determining target first class violation users in the first class of violation risk users.
6. The method according to claim 5, wherein the violation detecting account data of the first class of violation risk users and determining a target first class of violation users among the first class of violation risk users comprises:
acquiring historical user data generated by a user account number associated with the live broadcast platform by the first type of violation risk users;
and obtaining the target first-class violation users based on the first-class violation risk users with violation data in the historical user data.
7. The method according to claim 6, further comprising, after the obtaining of historical user data generated by the first type of violation risk user at a user account associated with the live platform:
calculating the violation risk degree of the first type of violation risk users according to the historical user data;
and obtaining the target first-class illegal users based on the first-class illegal users with the illegal risk degrees larger than the preset illegal risk degrees.
8. The method of claim 1, wherein obtaining a second class of users that have interacted with the first class of offending users in the live platform comprises:
acquiring a second type of candidate users which interact with the first type of illegal users in the live broadcast platform;
and determining the second class of users from the second class of candidate users according to the historical interaction frequency of the second class of candidate users and the first class of illegal users.
9. The method of claim 8, further comprising:
and carrying out violation detection on the account data of the second class of users, and determining target second class violation users in the second class of users.
10. The method of claim 1, further comprising:
determining the violation level of the target first-class violation users according to the violation information of the target first-class violation users;
and managing the target first-class violation users based on violation management information corresponding to the violation levels.
11. An apparatus for managing a live platform, the apparatus comprising:
the system comprises a first determining unit, a second determining unit and a third determining unit, wherein the first determining unit is used for determining first illegal users with historical illegal behaviors in the first users of a live broadcast platform, and the first users are either anchor users or audience users;
an obtaining unit, configured to obtain a second class of users who have interacted with the first class of illegal users in the live broadcast platform, where the second class of users is the other of the anchor user or the audience user;
and the prediction unit is used for predicting to obtain a first class of violation risk users based on the first class of users who have interacted with the second class of users on the live broadcast platform.
12. A computer device comprising a memory, a processor and a computer program stored on the memory and run on the processor, wherein the processor when executing the program implements a method of managing a live platform as claimed in any one of claims 1 to 10.
13. A storage medium storing a plurality of instructions adapted to be loaded by a processor to perform a method of managing a live platform according to any one of claims 1 to 10.
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