System and method for distributor analysis

Abstract

To provide systems or methods to help distributors analyze their own performance so that the distributors can do better in the next live streaming.SOLUTION: A method for distributor analysis includes: determining a first group of distributors corresponding to a first range of achievement scores; determining a second group of distributors corresponding to a second range of achievement scores; comparing a value of a stream parameter of a distributor from the second group of distributors with an average value of the stream parameter of the first group of distributors; and informing the distributor of a result of the comparison.SELECTED DRAWING: Figure 13

Description

[Technical field]

[0001] The present invention relates to stream analysis in the streaming field. [Background technology]

[0002] As exemplified by live streaming services, real-time communication over the Internet has become a part of everyday life. A variety of platforms and providers offer live streaming services, and competition is fierce. It is important for platforms to provide services that users want.

[0003] Patent Document 1 discloses a system and method for monitoring the quality of live video distribution. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] China Patent Application Publication No. 113747188 Summary of the Invention

[0005] A method according to one embodiment of the present invention is a method of broadcaster analysis implemented by one or more computers, comprising the steps of: determining a first group of broadcasters corresponding to a first range of achievement scores; determining a second group of broadcasters corresponding to a second range of achievement scores; comparing a value of a stream parameter of a broadcaster in the second group of broadcasters with an average value of the stream parameter of the first group of broadcasters; and informing the broadcaster of the result of the comparison.

[0006] A system according to one embodiment of the present invention is a system for broadcaster analysis including one or more processors, wherein the one or more computer processors execute machine-readable instructions to perform the following functions: determining a first group of broadcasters corresponding to a first range of achievement scores; determining a second group of broadcasters corresponding to a second range of achievement scores; comparing a value of a stream parameter of a broadcaster in the second group of broadcasters with an average value of the stream parameter of the first group of broadcasters; and notifying the broadcaster of the result of the comparison.

[0007] A computer-readable medium according to one embodiment of the present invention is a non-transitory computer-readable medium including a program for broadcaster analysis, the program causing one or more computers to perform the following functions: determining a first group of broadcasters corresponding to a first range of achievement scores; determining a second group of broadcasters corresponding to a second range of achievement scores; comparing a value of a stream parameter of a broadcaster in the second group of broadcasters with an average value of the stream parameter of the first group of broadcasters; and notifying the broadcaster of the result of the comparison. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a schematic diagram showing a configuration of a live streaming system 1 according to some embodiments of the present invention. [Diagram 2] 6 is a block diagram illustrating the functionality and configuration of the user terminal 30 of FIG. 5 in accordance with some embodiments of the present invention. [Diagram 3] 2 is a block diagram illustrating the functionality and configuration of the server of FIG. 1 in accordance with some embodiments of the present invention. [Figure 4] 4 is a table showing an example data structure of the stream DB 310 of FIG. 3. [Diagram 5] 4 is a table illustrating an example data structure of the user DB 312 of FIG. 3. [Figure 6] 4 is a table showing an example data structure of the gift DB 314 of FIG. 3. [Figure 7]4 is a table showing a data structure of an example of data stored in a user DB 312 of FIG. 3. [Figure 8] 4 is a table showing an example of a data structure of data stored in the stream parameter DB 350 of FIG. 3. [Figure 9] 4 is a table showing a data structure of an example of data stored in the analysis result DB 352 of FIG. 3. [Figure 10] 11 is an example of a performance suggestion notification to a publisher according to some embodiments of the present invention. [Figure 11] 4 is a table showing a data structure of an example of data stored in the action DB 354 of FIG. 3. [Figure 12] FIG. 1 is a schematic diagram illustrating an example of a real-time dashboard during live streaming. [Figure 13] 1 is an exemplary flow chart illustrating a method according to some embodiments of the present invention. [Figure 14] 1 is an exemplary flow chart illustrating a method according to some embodiments of the present invention. [Figure 15] 1 is a block diagram showing an example of a hardware configuration of an information processing device according to some embodiments of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, the same or similar components, parts, steps, or signals shown in each drawing will be denoted by the same reference numerals in all drawings, and duplicated explanations will be omitted as appropriate. In addition, some parts that are not important in the explanation of each drawing will be omitted.

[0010] It is desirable for content platforms to provide tools to content distributors (or streamers, live streamers) that help them review their past performance and improve their performance in the future. The present invention provides a system or method to help a distributor analyze their performance and help the distributor improve in their next live stream.

[0011] FIG. 1 is a schematic diagram showing a configuration of a live streaming system 1 according to some embodiments of the present invention. The live streaming system 1 provides a live streaming service for streaming streamers (also called live streamers, anchors, distributors, and live streamers) LV and viewers (also called audiences) AU (AU1, AU2, ...) to interact or communicate in real time. As shown in FIG. 1, the live streaming system 1 includes a server 10, a user terminal 20, and a user terminal 30 (30a, 30b, ...). In some embodiments, the streamers and viewers may be collectively referred to as users. The server 10 may include one or more information processing devices connected to a network NW. The user terminals 20 and 30 may be, for example, mobile terminal devices such as smartphones, tablets, notebook PCs, recorders, portable game consoles, and wearable terminals, or stationary devices such as desktop PCs. The server 10, the user terminals 20, and the user terminals 30 are connected to each other so as to be able to communicate with each other via various wired or wireless networks NW.

[0012] The live streaming system 1 includes a distributor LV, a viewer AU, and an administrator (or an app provider, not shown) who manages the server 10. The distributor LV is a person who distributes the content in real time by recording the content on his / her user terminal 20 and uploading it directly or indirectly to the server 10. Examples of the content may be the distributor's own song, talk, performance, game play, or any other content. The administrator provides a platform for live streaming the content on the server 10, and mediates or manages real-time interactions between the distributor LV and the viewer AU. The viewer AU accesses the platform with his / her user terminal 30, selects and watches desired content. During the live streaming of the selected content, the viewer AU performs operations such as sending comments, cheers, and gifts via the user terminal 30. The distributor LV who distributes the content may respond to those comments, cheers, or gifts. The response is transmitted to the viewer AU by video and / or audio, and two-way communication is established.

[0013] The term "live streaming" may refer to a data transmission mode that allows the content recorded at the user terminal 20 of the distributor LV to be played back and viewed at the user terminal 30 of the viewer AU in substantially real time, or may refer to a live broadcast realized by such a transmission mode. The live streaming may be realized by utilizing existing live streaming technologies such as HTTP live streaming, CMAF (Common Media Application Format), WebRTC (Web Real-Time Communications), RTMP (Real-Time Messaging Protocol), MPEG DASH, etc. Live streaming includes a transmission mode that allows the viewer AU to view the content with a predetermined delay at the same time as the content is recorded by the distributor LV. The length of the delay may be a delay that allows interaction between the distributor LV and the viewer AU. The live streaming is distinguished from so-called on-demand distribution, in which all recorded data of the content is stored once on the server and then provided to the user from the server upon the user's request.

[0014] The term "video data" as used herein refers to data including image data (also called video data) generated using the imaging function of the user terminal 20 or 30, and audio data generated using the audio input function of the user terminal 20 or 30. The video data is played on the user terminal 20, 30 so that the user can view the content. In some embodiments, it is assumed that the video data is subjected to a process such as compression, decompression, encoding, decoding, transcoding, etc., to change its format, size, or data specifications between the generation of the video data on the distributor's user terminal and the playback of the video data on the viewer's user terminal. However, since the content (e.g., video and audio) represented by the video data does not substantially change before and after such a process, the video data after such a process is expressed in this specification as being the same as the video data before such a process. In other words, when video data is generated at the distributor's user terminal and then played at the viewer's user terminal via the server 10, the video data generated at the distributor's user terminal, the video data passing through the server 10, and the video data received and played at the viewer's user terminal are all the same video data.

[0015] In the example shown in Fig. 1, the distributor LV provides live streaming data. The user terminal 20 of the distributor LV records video and audio of the distributor LV to generate the streaming data, and the generated data is transmitted to the server 10 via the network NW. At the same time, the user terminal 20 displays the recorded video VD of the distributor LV on the display of the user terminal 20, allowing the user to check the live streaming content currently being provided by the distributor LV.

[0016] The user terminals 30a, 30b of the viewers AU1, AU2 who have requested the platform to view the live streaming of the distributor LV receive video data related to the live streaming (hereinafter, may be referred to as "live streaming video data") via the network NW, play the received video data, display the videos VD1, VD2 on the display, and output audio from the speaker. The videos VD1, VD2 displayed on the user terminals 30a, 30b are substantially the same as the video VD captured by the user terminal 20 of the distributor LV, and the audio output from the user terminals 30a, 30b is substantially the same as the audio recorded by the user terminal 20 of the distributor LV.

[0017] The recording of video and audio on the user terminal 20 of the distributor LV and the playback of video data on the user terminals 30a and 30b of the viewers AU1 and AU2 are performed substantially simultaneously. When the viewer AU1 inputs a comment on the content provided by the distributor LV to the user terminal 30a, the server 10 displays the comment on the user terminal 20 of the distributor LV in real time, and also displays the comment on the user terminals 30a and 30b of the viewers AU1 and AU2. When the distributor LV reads the comment and develops a talk corresponding to the comment, the video and audio of the talk are displayed on the user terminals 30a and 30b of the viewers AU1 and AU2, respectively. This interactive operation is recognized as a conversation being established between the distributor LV and the viewer AU1. As a result, the live streaming system 1 realizes live streaming that enables two-way communication, not one-way communication.

[0018] FIG. 2 is a block diagram showing the functions and configuration of the user terminal 30 of FIG. 5 according to some embodiments of the present invention. The user terminal 20 has the same or similar functions and configuration as the user terminal 30. Each block of FIG. 2 and the following block diagrams may be realized by hardware elements such as a computer CPU or a mechanical device, or by software elements such as a computer program. The functional blocks may be realized by the cooperation of these elements. Therefore, it will be understood by those skilled in the art that these functional blocks may be realized in various forms by combining hardware and software.

[0019] The distributor LV and the viewer AU may download a live streaming application program (hereinafter, referred to as a live streaming application) from a download site via the network NW and install it on the user terminals 20 and 30. Alternatively, the live streaming application may be pre-installed on the user terminals 20 and 30. When the live streaming application is executed on the user terminals 20 and 30, the user terminals 20 and 30 communicate with the server 10 via the network NW and implement or execute various functions. Hereinafter, functions implemented by the user terminals 20 and 30 (processors such as CPUs) on which the live streaming application is executed will be described as functions of the user terminals 20 and 30. These functions are actually realized by the live streaming application on the user terminals 20 and 30. In some embodiments, these functions may be realized by a computer program written in a programming language such as HTML (HyperText Markup Language), transmitted from the server 10 to a web browser of the user terminals 20 and 30 via the network NW, and executed by the web browser.

[0020] The user terminal 30 includes a distribution unit 100 and a viewing unit 200. The distribution unit 100 generates video data in which the video and audio of the user (or the user side) are recorded, and provides the video data to the server 10. The viewing unit 200 receives the video data from the server 10 and plays the video data. The user starts the distribution unit 100 when performing live streaming, and starts the viewing unit 200 when the user watches a video. The user terminal on which the distribution unit 100 is started is the terminal of the distributor, i.e., the user terminal that generates the video data. The user terminal on which the viewing unit 200 is started is the terminal of the viewer, i.e., the user terminal on which the video data is reproduced and played.

[0021] The delivery unit 100 includes an imaging control unit 102, an audio control unit 104, a video transmission unit 106, and a distributor-side UI control unit 108. The imaging control unit 102 is connected to a camera (not shown in FIG. 2) and controls imaging performed by the camera. The imaging control unit 102 acquires image data from the camera. The audio control unit 104 is connected to a microphone (not shown in FIG. 2) and controls audio input from the microphone. The audio control unit 104 acquires the audio data from the microphone. The video transmission unit 106 transmits the image data acquired by the imaging control unit 102 and the video data including the audio data acquired by the audio control unit 104 to the server 10 via the network NW. The video data is transmitted in real time by the video transmission unit 106. That is, the generation of the video data by the imaging control unit 102 and the audio control unit 104 and the transmission of the generated video data by the video transmission unit 106 are performed substantially simultaneously. The distributor's UI control unit 108 controls the UI (user interface) of the distributor. The distributor's UI control unit 108 may be connected to a display (not shown in FIG. 2) and displays a video on the display by playing the video data transmitted by the video transmission unit 106. The distributor's UI control unit 108 may display an operation object or an instruction permission object on the display and accept an input from the distributor who taps on the object.

[0022] The viewing unit 200 includes a viewer-side UI control unit 202, an overlay information generating unit 204, and an input information transmitting unit 206. The viewing unit 200 receives video data related to live streaming in which the distributor, the viewer who is the user of the user terminal 30, and other viewers participate from the server 10 via the network NW. The viewer-side UI control unit 202 controls the UI of the viewer. The viewer-side UI control unit 202 is connected to a display and a speaker (not shown in FIG. 2), plays the received video data, displays the video on the display, and outputs the audio from the speaker. The state in which the video is output to the display and the audio is output from the speaker can be called a "video data is being played" state. The viewer-side UI control unit 202 is also connected to an input means (not shown in FIG. 2) such as a touch panel, a keyboard, a display, etc., and acquires a user's input via the input means. The overlay information generating unit 204 overlays a predetermined frame image on an image generated from video data from the server 10. The frame image includes various user interface objects (hereinafter simply referred to as "objects") for receiving input from the user, comments entered by the viewer, and / or information acquired from the server 10. The input information transmitting unit 206 transmits the user input acquired by the viewer-side UI control unit 202 to the server 10 via the network NW.

[0023] Figure 3 shows a block diagram illustrating the function and configuration of the server 10 of Figure 1 according to some embodiments of the present invention. The server 10 includes a delivery information providing unit 302, a relay unit 304, a gift processing unit 306, a payment processing unit 308, a stream DB 310, a user DB 312, a gift DB 314, a user grouping unit 330, a stream analysis unit 332, a stream parameter DB 350, an analysis result DB 352, and an action DB 354. The server 10 communicates with a machine learning (ML) DB 370. In some embodiments, the machine learning DB 370 may be implemented in the server 10.

[0024] When a notification or request to start live streaming is received from the user terminal 20 on the distributor side via the network NW, the distribution information providing unit 302 registers in the stream DB 310 a stream ID for identifying the live streaming and the distributor ID of the distributor performing the live streaming.

[0025] When the distribution information providing unit 302 receives a request for providing information about live streams from the viewing unit 200 of the user terminal 30 on the viewer side via the network NW, the distribution information providing unit 302 obtains or checks currently available live streams from the stream DB 310, and creates a list of available live streams. The distribution information providing unit 302 transmits the created list to the requesting user terminal 30 via the network NW. The viewer side UI control unit 202 of the requesting user terminal 30 generates a live stream selection screen based on the received list, and displays it on the display of the user terminal 30.

[0026] When the input information sending unit 206 of the user terminal 30 receives the selection result of the viewer on the live stream selection screen, the input information sending unit 206 generates a delivery request including the stream ID of the selected live stream and sends the request to the server 10 via the network NW. The delivery information providing unit 302 starts providing the live stream specified by the stream ID included in the received delivery request to the requesting user terminal 30. The delivery information providing unit 302 updates the stream DB 310 so that the viewer ID of (or the corresponding) the stream ID includes the user ID of the viewer of the requesting user terminal 30.

[0027] The relay unit 304 relays the video data from the user terminal 20 on the distributor side to the user terminal 30 on the viewer side in the live streaming started by the distribution information providing unit 302. The relay unit 304 receives a signal representing a user input by a viewer from the input information transmitting unit 206 during the live streaming or during playback of the video data. The signal representing the user input may be an object designation signal that designates an object displayed on the display of the user terminal 30. The object designation signal may include a viewer ID of the viewer, a distributor ID of the distributor of the live stream that the viewer is viewing, and an object ID that identifies the object. When the object is a gift, the object ID is a gift ID. Similarly, the relay unit 304 receives a signal representing a user input made by a distributor during playback (or live streaming) of the video data from the distribution unit 100 of the user terminal 20. The signal may be an object designation signal.

[0028] Furthermore, the signal representing the user input may be a comment input signal including a comment input by a viewer to the user terminal 30 and the viewer ID of the viewer. Upon receiving the comment input signal, the relay unit 304 transmits the comment and the viewer ID included in the signal to the user terminal 20 of the distributor and the user terminals 30 of other viewers. In these user terminals 20, 30, the viewer-side UI control unit 202 and the overlay information generation unit 204 display the received comment on a display associated with the viewer ID that has also been received.

[0029] The gift processing unit 306 increases the points of the distributor based on the points of the gift specified by the gift ID included in the object designation signal, and updates the user DB 312. Specifically, the gift processing unit 306 refers to the gift DB 314 to specify the points to be given to the gift ID included in the received object designation signal. Then, the gift processing unit 306 updates the user DB 312 and adds the specified points to the points of the distributor ID (or corresponding to the distributor ID) included in the object designation signal.

[0030] In response to receiving the object designation signal, the payment processing unit 308 processes the payment of the gift from the viewer. Specifically, the payment processing unit 308 refers to the gift DB 314 to determine the price points of the gift identified by the gift ID included in the object designation signal. Then, the payment processing unit 308 updates the user DB 312 and subtracts the determined price points from the points of the viewer identified by the viewer ID included in the object designation signal.

[0031] FIG. 4 is a table showing an exemplary data structure of the stream DB 310 of FIG. 3. The stream DB 310 holds information about a live stream currently being performed. The stream DB 310 stores a stream ID, a broadcaster ID, and a viewer ID in a mutually associated manner. The stream ID is an ID for identifying a live stream in a live streaming platform provided by the live streaming system 1. The broadcaster ID is a user ID for identifying a broadcaster providing the live stream. The viewer ID is a user ID for identifying a viewer of the live stream. In a live streaming platform provided by the live streaming system 1 according to some embodiments, when a user starts a live stream, the user becomes a broadcaster, and when the same user watches a live stream broadcasted by another user, the user also becomes a viewer. Therefore, the distinction between a broadcaster and a viewer is not fixed, and a user ID registered as a broadcaster ID at one time may be registered as a viewer ID at another time.

[0032] FIG. 5 is a table showing an exemplary data structure of the user DB 312 of FIG. 3. The user DB 312 holds information about users. The user DB 312 stores the user ID and the points in a mutually associated manner. The user ID identifies a user. The points correspond to points held by the corresponding user. The points are electronic values ​​circulating within the live streaming platform. In some embodiments, when a broadcaster receives a gift from a viewer during a live broadcast, the broadcaster's points increase by a value corresponding to the gift. The points are used, for example, to determine the amount of compensation (such as money) that the broadcaster receives from the administrator of the live streaming platform. In some embodiments, when the broadcaster receives a gift from a viewer, an amount corresponding to the gift may be given instead of the points.

[0033] FIG. 6 is a table showing an exemplary data structure of the gift DB 314 of FIG. 3. The gift DB 314 holds information about gifts available to the viewer during the live streaming. Gifts are electronic data. Gifts may be purchased with points or money, or may be provided free of charge. Gifts may be given to the broadcaster by the viewer. Giving a gift to the broadcaster is also called using a gift, sending a gift, throwing a gift, etc. Some gifts can be used immediately after purchase, while others can be used at any time after purchase by the viewer who purchased the gift. When a viewer gives a gift to a broadcaster, the broadcaster is given an amount of points corresponding to the gift. When a gift is used, an effect related to the gift may occur as a result of the use. For example, an effect (such as a visual effect or an auditory effect) corresponding to the gift is displayed on the live streaming screen.

[0034] The gift DB 314 stores a gift ID, an assignment point, and a price point in association with each other. The gift ID is for identifying a gift. The assignment point is the amount of points that is assigned to a broadcaster when the gift is given to the broadcaster. The price point is the amount of points paid for the use (purchase) of the gift. A viewer can give a desired gift to a broadcaster by paying the price points of the desired gift while watching a live stream. The payment of the price points can be made by an appropriate electronic payment means. For example, the viewer may pay the price points to the administrator. Alternatively, payment by bank transfer or credit card may be used. The administrator can arbitrarily set the relationship between the assignment points and the price points. For example, it may be set as assignment points = price points. Alternatively, it may be set as the price points obtained by multiplying the assignment points by a predetermined coefficient such as 1.2, or as the price points obtained by adding a predetermined fee point to the assignment points.

[0035] FIG. 7 is a table showing a data structure of an example of data stored in the user DB 312 of FIG. 3. The user DB 312 stores a broadcaster ID, an achievement parameter, an achievement score, a group level, and a time series in association with each other. In this embodiment, the achievement parameter includes the broadcaster's followers and the points received. In some embodiments, the achievement parameter may include other indicators, such as the revenue contributed by the corresponding broadcaster. The achievement score is calculated from the achievement parameter. In this embodiment, the achievement score is set to be equal to the points received. In other embodiments, the achievement score may be set according to the actual operation or the focus of the streaming platform operator. For example, the achievement score may increase with an increase in one or more achievement parameters. For example, the achievement score may be proportional to one or more achievement parameters. For example, the achievement score may be a weighted sum of the achievement parameters.

[0036] The group level corresponds to the grouping result of the broadcaster at a certain time and is determined based on the achievement score. For example, in this embodiment, the group level G1 corresponds to the achievement score range of 0 to 9999, the group level G2 corresponds to the achievement score range of 10000 to 19999, and the group level G3 corresponds to the achievement score range of 20000 to 29999. The grouping process may be performed by the user grouping unit 330.

[0037] FIG. 8 is a table showing a data structure of an example of data stored in the stream parameter DB 350 of FIG. 3. The stream parameter DB 350 stores the broadcaster ID, the stream ID, and the stream parameters in association with each other. The stream parameters may include a broadcast duration, the number of comments from viewers during the broadcast, the number of clicks by viewers, the number of viewers (or gift senders) who gave gifts during the broadcast, the number of share actions by viewers during the broadcast, the number of poke actions (to viewers) of the broadcaster during the broadcast, the number of follow actions by viewers during the broadcast, the number of commenters during the broadcast, the number of viewers who watched the broadcast for a predetermined time or more, thumbnail data of the broadcast (e.g., click rate of image data or thumbnail), broadcast timing of the broadcast, and the like. In some embodiments, the stream parameters may include a broadcaster's absence time indicating a time when the broadcaster is not streaming. In some embodiments, the stream parameters may include any of the above elements within a predetermined time.

[0038] As shown in Figure 8, the average number of each stream parameter may be calculated. The calculation may be performed for a given time period. For example, streams performed by the broadcaster within the last week or within the last month may be included in the calculation.

[0039] The user grouping unit 330 is configured to divide or separate users into different groups based on the achievement scores of each user. For example, the user grouping unit 330 may determine a first group of broadcasters whose achievement scores correspond to a first range (such as a higher range). The user grouping unit 330 may determine a second group of broadcasters whose achievement scores correspond to a second range (such as a lower range). For example, the first group of broadcasters may receive more followers and / or more points. The second group of broadcasters may receive fewer followers and / or fewer points. The grouping result may be stored in the user DB 312, as shown in FIG. 7.

[0040] The stream analysis unit 332 is configured to analyze the performance of the broadcaster (or the stream of the broadcaster). The stream analysis unit 332 is configured to provide advice on the broadcaster's performance (or performance direction) based on the analysis results. The analysis may be based on the broadcaster's performance score, stream parameters of streams made by the broadcaster, performance scores of other broadcasters, and / or stream parameters of streams made by other broadcasters.

[0041] For example, the stream analysis unit 332 compares the value of the stream parameter of the broadcaster D1 belonging to the second broadcaster group (having a lower achievement score) with the average value of the stream parameter of the first broadcaster group (having a higher achievement score). The value of the stream parameter of the broadcaster D1 may be, for example, an average value calculated from multiple streams performed by the broadcaster D1. The stream analysis unit 332 then informs the broadcaster D1 of the result of the comparison process and informs the broadcaster D1 of the direction in which the broadcaster D1 should make efforts to improve the achievement score. The analysis result may be stored in the analysis result DB 352.

[0042] In some embodiments, the notification step may include displaying the difference between the stream parameter value of the broadcaster D1 and the average stream parameter value of the first broadcaster group after the broadcaster D1 finishes the stream. In some embodiments, the notification step may include displaying the difference between the real-time value of the stream parameter and the average stream parameter value of the first broadcaster group during the broadcaster D1's live broadcast. Thus, the broadcaster D1 can understand in real time how to improve the stream parameter to approach the performance of the broadcaster with a high achievement score (e.g., the first broadcaster group). In some embodiments, the notification step may include sending a notification to the broadcaster D1 about the comparison result. For example, the stream analysis unit 332 may send a notification request to a notification unit (in the server 10 or outside the server 10) to perform the notification step.

[0043] In some embodiments, the notification step may include providing the distributor with a suggested action. For example, the stream analysis unit 332 may reference the action DB 354 for the suggested action and display (or send a notification to) the distributor to encourage improvement.

[0044] Fig. 9 is a table showing a data structure of an example of data stored in the analysis result DB 352 of Fig. 3. The analysis result DB 352 stores the distributor ID, current level, next level, current performance value, target value (goal), difference, and suggestion in association with each other.

[0045] As shown in FIG. 9, for streamer D1, the current level is G1 and the next level (or target level) is G2. The stream parameters in the "Your Performance" row indicate the average value of each stream parameter for streamer D1, which may be calculated based on the stream parameters of multiple streams performed by streamer D1. The stream parameters in the "Your Goal" row indicate the average value of each stream parameter for group level G2, which may be calculated based on the average stream parameters of streamers in group level G2. The "Difference" row indicates the difference between the "Your Performance" row and the "Your Goal" row. The "Suggestion / Comment" row indicates performance suggestions for streamer D1 based on the difference between each stream parameter. The suggestions may include the content of the suggestion and / or the priority of the suggestion.

[0046] The "difference" may be expressed as a value or a percentage (relative to a target). A threshold may be defined for the difference. The threshold may be used to determine the content or priority of the suggestion. For example, a threshold of 50% may be defined for the difference, such that a difference (or negative difference) greater than 50% results in a priority 1 suggestion for the corresponding stream parameter. Another threshold may be defined for the difference, such as 20%, such that a difference (or negative difference) between 20% and 50% results in a priority 2 suggestion for the corresponding stream parameter. As shown in FIG. 9, streamer D1 is outperformed by G2 by more than 50% in the stream parameters "share" and "poke". Thus, these two parameters are shown as priority 1 for improvement.

[0047] FIG. 10 is an example of a performance suggestion notification to a publisher according to some embodiments of the present invention.

[0048] As shown in FIG. 10, the streamers are divided into groups (or group levels, or buckets) G3 (high achievement score), G2 (medium achievement score), and G1 (low achievement score). "Bucket criteria" indicates the respective criteria for each level. The streamers belonging to G3 are not sent educational push notifications (PN) regarding performance suggestions. The streamer D1 belonging to G2 is subjected to performance analysis based on the indicator values ​​(or stream parameters) of the streamer D1 and the average indicator values ​​of the streamers belonging to G3. The stream analysis unit 332 performs a comparison and finds "stream duration" and "poke", which are indicators for improving the performance of the streamer D1. Then, educational push notifications regarding the analysis results are sent to the streamer D1, for example, through the Braze notification service. Thus, the streamer D1 can know which part to improve to get closer to the next level. For example, the streamer D1 may need to increase the duration of the stream. For example, the streamer D1 may need to poke viewers more frequently during streaming.

[0049] Fig. 11 is a table showing an example of a data structure of data stored in the action DB 354 of Fig. 3. The action DB 354 stores the indicators (or stream parameters) and proposed actions in association with each other.

[0050] For example, the stream analysis unit 332 may compare stream parameters of the broadcaster D1 with the next group level and determine that the thumbnail of the broadcaster D1 is relatively bad. In some embodiments, a bad thumbnail may mean a low click-through rate. The click-through rate may be defined as the number of times the thumbnail was clicked divided by the number of times the thumbnail was displayed to viewers. In some embodiments, the thumbnail may be determined to be bad by a machine learning model (e.g., stored in the machine learning DB 370) based on its image data. The stream analysis unit 332 may then display a message to the broadcaster D1 saying, "By changing your thumbnail, you can attract more viewers and gain new viewers."

[0051] For example, the stream analysis unit 332 may compare the stream parameters of the broadcaster D1 with the next group level and determine that the broadcaster D1 has a relatively poor broadcast timing. A poor broadcast timing may mean a time when the target audience (for the broadcaster D1) on the platform is small. In some embodiments, the broadcast timing may be determined to be poor by a machine learning model (e.g., stored in the machine learning DB 370) based on the viewer's attribute data and / or viewing history. The stream analysis unit 332 may then display a message to the broadcaster D1 saying, "Broadcast in the next recommended time slot with a larger target audience: [time slot personalized for each broadcaster]." The time slot personalized for each broadcaster may be determined by a machine learning model.

[0052] For example, the stream analysis unit 332 may compare the stream parameters of broadcaster D1 with the next group level and determine that broadcaster D1 has been absent for a relatively long period (or longer than a threshold of X days, for example). The stream analysis unit 332 may then display a message to broadcaster D1 saying, "Your audience wants to see your performance. Stream this week."

[0053] In some embodiments, the stream analysis unit 332 determines the correlation between stream parameters and achievement scores, for example, by utilizing a machine learning model in the machine learning DB 370. For example, by calculating the correlation value between group-level stream parameters with high achievement scores and the achievement scores, it is possible to find the critical stream parameters that lead to high achievement scores. The stream analysis unit 332 then uses the correlation results to determine the action to suggest to the broadcaster.

[0054] For example, the stream analysis unit 332 compares the stream parameters of the broadcaster D1 with the next group level (or higher group level) and determines that the broadcaster D1 has a shorter broadcast duration and a smaller number of pokes. The stream analysis unit 332 then uses the correlation data to determine that pokes are more correlated or more decisive (than broadcast duration) to a high achievement score at the next group level. Thus, the stream analysis unit 332 suggests an action to increase the number of pokes for the broadcaster D1 with a higher priority.

[0055] In some embodiments, the data in the analytics DB 352 may be displayed to the corresponding broadcaster as a performance dashboard. For example, FIG. 9 (or a portion of FIG. 9) may be displayed to broadcaster D1 as a performance dashboard. Broadcaster D1 may select or pin any stream parameters that he or she wants to focus on on the dashboard. In some embodiments, the stream parameter values ​​of "Your Performance" may be real-time values ​​of a live stream being conducted by broadcaster D1. The "Difference" and "Suggestions" may change in real-time based on the real-time value of "Your Performance".

[0056] 12 is a schematic diagram showing an example of a real-time dashboard during live streaming. A broadcaster D1 sets stream parameters of "poke" and "share" in the dashboard of a live stream. The dashboard can help the broadcaster to focus more on improving important stream parameters. In some embodiments, the displayed parameters may be set by the stream analysis unit 332 based on stream analysis results.

[0057] FIG. 13 is an exemplary flow chart illustrating a method according to some embodiments of the present invention.

[0058] In step S1300, a publisher's performance score (from the publisher's performance parameters) is obtained or calculated.

[0059] In step S1302, the user grouping unit 330 categorizes the broadcasters into different group levels based on their achievement scores.

[0060] In step S1304, the attributes of the distributor are acquired. The attributes include information such as the distributor's gender, location (or country), language, time zone, distribution genre, distribution topic, streaming time, follower type (or type distribution), and viewer type (or viewer distribution). The attribute data may be stored in the user DB 312, for example.

[0061] In step S1306, for a publisher D1 belonging to group G1 (having a low achievement score), similar publishers belonging to group G2 (having a high achievement score) are determined (for example, by the user grouping unit 330). Similar publishers have one or more attributes similar (or the same) to publisher D1. Similarity matching or vector matching may be performed, for example, by machine learning model 370.

[0062] In step S1308, the stream parameters of the similar distributor are obtained.

[0063] In step S1310, the correlation value between the stream parameters and the achievement score for similar broadcasters is calculated to find important stream parameters that contribute to a high achievement score. This process may be performed by, for example, the stream analysis unit 332.

[0064] In step S1312, the values ​​of the important stream parameters are compared between distributor D1 and the similar distributors.

[0065] In step S1314, based on the comparison result in step S1312, stream parameters to be improved for the distributor D1 are determined.

[0066] In step S1316, the distributor D1 is notified of the comparison result and / or the stream parameters to be improved.

[0067] The similar distributor may have many viewers in common with or similar to the distributor D1. Therefore, by identifying the similar distributor, the parameters obtained may be more useful for improving the achievement score of the distributor D1 with higher accuracy.

[0068] FIG. 14 is an exemplary flow chart illustrating a method according to some embodiments of the present invention.

[0069] In step S1400, a publisher's performance score (from the publisher's performance parameters) is obtained or calculated.

[0070] In step S1402, the user grouping unit 330 classifies the broadcasters into different group levels based on their achievement scores.

[0071] In step S1404, the attributes of the distributor are obtained.

[0072] In step S1406, for a publisher D2 belonging to group G2 (having a high achievement score), similar publishers belonging to group G1 (having a low achievement score) are determined (for example, by the user grouping unit 330). Similar publishers have one or more attributes similar (or the same) to publisher D2. Similarity matching or vector matching may be performed, for example, by machine learning model 370.

[0073] In step S1408, the stream parameters of the similar distributor are obtained.

[0074] In step S1410, the stream parameters and the performance score correlations are calculated for the similar broadcasters to find important stream parameters that cause the performance score to decrease. This process may be performed by the stream analysis unit 332, for example.

[0075] In step S1412, the values ​​of the important stream parameters are compared between distributor D2 and the similar distributors.

[0076] In step S1414, based on the comparison result in step S1412, stream parameters that the distributor D2 should pay attention to are determined.

[0077] In step S1416, the distributor D2 is notified of the comparison results and / or the noteworthy stream parameters.

[0078] For example, in step S1410, it is determined that low delivery frequency is a decisive factor for the low achievement score of the distributors belonging to G1. Then, when the delivery frequency of distributor D2 drops or approaches the average delivery frequency of G1, distributor D2 receives a notification warning him not to drop (or maintain) his delivery frequency.

[0079] In many cases, the stream parameters that a streamer should improve (or focus on) to reach a higher level are not necessarily the same as the stream parameters that the streamer should pay attention to in order to avoid dropping to a lower level. When a streamer focuses on raising his / her level, he / she may not be aware of factors to maintain his / her current level (or avoid dropping to a lower level). The present invention can provide a behavioral goal for a streamer to raise his / her level (raise the achievement score), and also provide a warning to prevent the streamer from dropping his / her level (lowering the achievement score).

[0080] The hardware configuration of the information processing device will be described with reference to Fig. 15. Fig. 15 is a block diagram showing an example of the hardware configuration of an information processing device based on some embodiments of the present invention. The information processing device 900 shown in the figure can realize, for example, the server 10 and / or the user terminals 20 and 30 in some embodiments.

[0081] The information processing device 900 includes a CPU 901, a ROM (read only memory) 903, and a RAM (random access memory) 905. The information processing device 900 may also include a host bus 907, a bridge 909, an external bus 911, an interface 913, an input device 915, an output device 917, a storage device 919, a drive 921, a connection port 925, and a communication device 929. The information processing device 900 further includes an imaging device such as a camera (not shown). The information processing device 900 may also include a DSP (digital signal processor) or an ASIC (application specific integrated circuit) in addition to or instead of the CPU 901.

[0082] The CPU 901 functions as an arithmetic processing device and a control device, and controls all or part of the operation of the information processing device 900 according to various programs stored in the ROM 903, the RAM 905, the storage device 919, or the removable recording medium 923. For example, the CPU 901 controls the overall operation of each functional unit included in the server 10 and the user terminals 20 and 30 in some embodiments. The ROM 903 stores programs and arithmetic parameters used by the CPU 901. The RAM 905 functions as a main storage device that stores programs used when the CPU 901 is executed, parameters that change appropriately during execution, and the like. The CPU 901, the ROM 903, and the RAM 905 are interconnected by a host bus 907, which may be an internal bus such as a CPU bus. Furthermore, the host bus 907 is connected to an external bus 911 such as a PCI (Peripheral Component Interconnect / Interface) bus via a bridge 909.

[0083] The input device 915 may be a device operated by a user, such as a mouse, a keyboard, a touch panel, a button, a switch, or a lever, or a device that converts a physical quantity into an electric signal, such as a sound sensor represented by a microphone, an acceleration sensor, a tilt sensor, an infrared sensor, a depth sensor, a temperature sensor, or a humidity sensor. The input device 915 may be, for example, a remote control device that uses radio waves such as infrared rays, or an external connection device 927 such as a mobile phone that supports the operation of the information processing device 900. The input device 915 includes an input control circuit that generates an input signal based on information input by the user or a detected physical quantity and outputs the input signal to the CPU 901. The user operates the input device 915 to input various data to the information processing device 900 and instruct the information processing device 900 to operate.

[0084] The output device 917 is a device that can visually or audibly notify the user of acquired information. The output device 917 may be, for example, a display such as an LCD, a PDP, or an OLED, an audio output device such as a speaker or a headphone, or a printer. The output device 917 outputs the processing result by the information processing device 900 as a video such as text or an image, or an audio such as a voice.

[0085] The storage device 919 is a data storage device and is configured as an example of a storage unit of the information processing device 900. The storage device 919 is, for example, a magnetic storage device such as a hard disk drive (HDD), a semiconductor storage device, an optical storage device, or a magneto-optical storage device. The storage device 919 stores the programs executed by the CPU 901, various data, various data acquired from the outside, and the like.

[0086] The drive 921 is a reader / writer of a removable recording medium 923 such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, and is built into or externally attached to the information processing device 900. The drive 921 reads out information recorded on the attached removable recording medium 923, and outputs it to the RAM 905. Furthermore, the drive 921 writes information to the attached removable recording medium 923.

[0087] The connection port 925 is a port for directly connecting a device to the information processing device 900. The connection port 925 may be, for example, a USB (Universal Serial Bus) port, an IEEE1394 port, or a SCSI (Small Computer System Interface) port. Furthermore, the connection port 925 may be an RS-232C port, an optical audio terminal, an HDMI (registered trademark) (High Definition Multimedia Interface) port, or the like. By connecting the external connection device 927 to the connection port 925, various data can be exchanged between the information processing device 900 and the external connection device 927.

[0088] The communication device 929 is, for example, a communication interface formed by a communication device for connecting to the network NW. The communication device 929 may be, for example, a communication card for a wired or wireless local area network (LAN), Bluetooth (trademark), or wireless USB (WUSB). Furthermore, the communication device 929 may be a router for optical communication, a router for ADSL (asymmetric digital subscriber line), or a modem for various communications. The communication device 929 transmits and receives signals, etc., on the Internet or between other communication devices using a predetermined protocol such as TCP / IP. The communication network NW connected to the communication device 929 is a network connected by wire or wirelessly, for example, the Internet, a home LAN, infrared communication, radio wave communication, satellite communication, etc. The communication device 929 realizes a function as a communication device.

[0089] The imaging device (not shown) is a device that captures an image of real space using an imaging element such as a CCD (charge-coupled device) or a CMOS (complementary metal-oxide semiconductor) and various members such as a lens for controlling the formation of a subject image on the imaging element, and generates a captured image. The imaging device may capture still images or moving images.

[0090] The configuration and operation of the live streaming system 1 according to this embodiment have been described above. This embodiment is merely an example, and it will be understood by those skilled in the art that various modifications are possible with respect to the combination of each component and each process, and that such modifications are also within the scope of the present invention.

[0091] The processes and procedures described in the present invention can be realized by software, hardware, or any combination thereof, in addition to those explicitly described. For example, the processes and procedures described herein can be realized by implementing logic corresponding to the processes and procedures in a medium such as an integrated circuit, a volatile memory, a non-volatile memory, a non-transitory computer-readable medium, a magnetic disk, etc. Furthermore, the processes and procedures described herein can be realized as a computer program corresponding to the processes and procedures, and can be executed by various computers.

[0092] Furthermore, the system or method described in the above embodiments may be integrated into a program stored in a non-transitory computer-readable medium such as a solid-state storage device, an optical disk storage device, a magnetic disk storage device, etc. Alternatively, the program may be downloaded from a server via the Internet and executed by a processor.

[0093] Although the technical contents and features of the present invention have been described above, those skilled in the art can still make many variations and modifications without departing from the teachings and disclosure of the present invention. Therefore, the scope of the present invention is not limited to the embodiments already disclosed, but is within the scope of the claims, including other variations and modifications that do not depart from the present invention. [Explanation of symbols]

[0094] 1. Communication Systems 10 Server 20 User terminal 30, 30a, 30b User terminal LV Streamer AU1, AU2 viewers VD, VD1, VD2 Video NW Network 30 User terminals 100 Delivery Units 102 Imaging control unit 104 Audio control unit 106 Video transmission unit 108 Provider UI Control Unit 200 viewing units 202 Viewer side UI control unit 204 Superposition Information Generation Unit 206 Input information transmission unit 302 Distribution Information Unit 304 Relay unit 306 Gift Processing Unit 308 Payment Processing Unit 310 Stream DB 312 User DB 314 Gift DB 330 User Grouping Unit 332 Stream Analysis Unit 350 Stream Parameter DB 352 Analysis result DB 354 Action DB 370 Machine Learning DB S1300, S1302, S1304, S1306, S1308, S1310, S1312, S1314, S1316 process S1400, S1402, S1404, S1406, S1408, S1410, S1412, S1414, S1416 process 900 Information processing device 901 CPU 903 ROM 905 RAM 907 Host Bus 909 Bridge 911 External Bus 913 Interface 915 Input Device 917 Output Device 919 Storage Device 921 Drive 923 Removable Recording Media 925 Connection Port 927 External connection device 929 Communication Equipment

Claims

1. A method for analyzing a distributor in a streaming platform, the method being executed by a server, comprising: determining a first group of publishers corresponding to a first range of achievement scores; determining a second group of publishers corresponding to a second range of achievement scores; comparing a value of a stream parameter of a broadcaster of the second group of broadcasters with an average value of the stream parameter of the first group of broadcasters; notifying the distributor of the results of the comparison; A distributor analysis method comprising:

2. The method of analyzing broadcasters described in claim 1, characterized in that the achievement score of a first broadcaster increases as the number of followers of the first broadcaster increases or as the number of points received by the first broadcaster increases.

3. 2. The method of claim 1, wherein the stream parameters correspond to an average duration per stream, an average number of comments per stream, an average number of gift senders per stream, an average number of shares per stream, an average number of pokes per stream, an average number of comments per stream, or an average number of viewers who watch for a predetermined time or more per stream.

4. The method of claim 1, further comprising: determining, by a machine learning model, that the stream parameter is correlated with the first range of achievement scores based on the values ​​of the stream parameters of the first group of broadcasters and the first range of achievement scores.

5. 2. The method of claim 1, wherein the notification step includes displaying, during a live stream of a broadcaster from the second group of broadcasters, a difference between a real-time value of the stream parameter of the broadcaster and an average value of the stream parameter of the first group of broadcasters.

6. 2. The method of claim 1, further comprising the step of determining that the broadcasters from the first broadcaster group and the second broadcaster group have the same attributes.

7. 2. The method of claim 1, wherein the first range of achievement scores is higher than the second range of achievement scores, and the results include suggested actions for the broadcaster to increase the broadcaster's stream parameters.

8. 2. The method of claim 1, wherein the first range of achievement scores is lower than the second range of achievement scores, and the result includes a warning to the broadcaster to avoid lowering the stream parameters of the broadcaster.

9. 1. A system for broadcaster analysis, comprising: one or more processors, the one or more processors executing machine-readable instructions to: determining a first group of publishers corresponding to a first range of achievement scores; determining a second group of publishers corresponding to a second range of achievement scores; a function for comparing a value of a stream parameter of a publisher of the second group of publishers with an average value of the stream parameter of the first group of publishers; a function of notifying the distributor of the result of the comparison; A system for distributor analysis, comprising:

10. A non-transitory computer readable medium containing a program for distributor analysis, wherein the program is configured to: determining a first group of publishers corresponding to a first range of achievement scores; determining a second group of publishers corresponding to a second range of achievement scores; a function for comparing a value of a stream parameter of a publisher of the second group of publishers with an average value of the stream parameter of the first group of publishers; a function of notifying the distributor of the result of the comparison; 23. A computer-readable medium for causing a computer to execute a program.

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