CN110636344A - Program evaluation method based on new media multi-source cross-screen data analysis - Google Patents
Program evaluation method based on new media multi-source cross-screen data analysis Download PDFInfo
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- CN110636344A CN110636344A CN201810666203.2A CN201810666203A CN110636344A CN 110636344 A CN110636344 A CN 110636344A CN 201810666203 A CN201810666203 A CN 201810666203A CN 110636344 A CN110636344 A CN 110636344A
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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
- H04N21/251—Learning process for intelligent management, e.g. learning user preferences for recommending movies
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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
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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]
- H04N21/40—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
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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]
- H04N21/40—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
- H04N21/466—Learning process for intelligent management, e.g. learning user preferences for recommending movies
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- Computing Systems (AREA)
- Testing, Inspecting, Measuring Of Stereoscopic Televisions And Televisions (AREA)
Abstract
A program evaluation method based on new media multisource cross-screen data analysis comprises the steps of firstly collecting multiscreen behavior data of intelligent terminal users such as DVB (digital video broadcasting) bidirectional terminals, IPTV (Internet protocol television), OTT (over the top of the bottom of. The method provided by the invention obtains mass multi-screen behavior data of the users with the most economic investment, quickly, effectively and accurately analyzes the user attribute information, and obtains the personnel outline and the behavior trend of the users.
Description
The technical field is as follows:
the invention relates to the internet information processing technology, in particular to a program evaluation method based on new media multi-source cross-screen data analysis.
Background art:
in the age of media fusion, the rapid development of cross-media propagation changes the pattern of the media market deeply, and influences the entertainment and living habits of people. More and more people watch videos across screens at any time and any place through terminals such as computers, mobile phones, PADs and the like. The television time-shifting viewing and the network terminal viewing become new choices for viewers to watch various programs outside the television live broadcast, various viewing terminals construct a multi-screen world, the viewing behaviors of the viewers are not only limited on one television screen, and the practice of only investigating the viewing rate of the television screen is not good at all times. In the multi-screen era, the evaluation program needs to consider not only the behavior index and opinion index of the television screen, but also the audience watching behavior and watching opinions on other terminals, namely, the multi-screen index. The traditional audience rating survey evaluation method is in urgent need of time-varying, and no matter a television station, an advertising company or an advertiser urgently needs an effective audience rating survey system capable of carrying out cross-screen multi-dimensional evaluation so as to more clearly understand audiences and grasp market development trend.
Meanwhile, the evaluation standard and method are different, and the evaluation result is different, so that the influence on the program is different. In terms of the current situation of the evaluation and development of television programs in China, the evaluation mode mainly comprises government-oriented propaganda value evaluation, commercial-oriented economic value evaluation and research-oriented cultural value evaluation, namely public opinion, audience rating and satisfaction. In any mode of program evaluation, qualitative or quantitative systematic evaluation and evaluation should be performed on the value of the program and its influence and various factors bearing the program value according to the principles of objective, fair, scientific and real. The final purpose of program evaluation is to provide guidance, reference and reference for program producers, thereby improving the spreading effect and comprehensive benefit of programs. Being the primary program producer, the subject being evaluated, the participation of broadcast television media in the primary program evaluation system is severely compromised. The limitations and disadvantages of commercial program evaluation mode with audience rating as the core have been known and suffered by the industry, but the missing program evaluation is used as one of the reference indexes for performance evaluation of television media workers, and is related to the personal interests of the broadcast and television station workers.
From the existing broadcast television program evaluation system, China basically inherits the basic modes of American commercial audience rating survey and British appreciation index survey, and then selects corresponding indexes according to the national conditions and the actual conditions of each station of China. However, because of the numerous broadcast television stations in China, different administrative levels and economic strength, which are 'marks' respectively, the evaluation objects are diverse and different in standard, the evaluation objects (or indexes) are not homologous or synchronous, the index weight is random, the system is disordered and lacks comparability and universality; the integrity and the uniformity of the broadcast television program industry and the market in China cannot simultaneously accept a five-flower eight-door program evaluation system. Therefore, how to create a program evaluation system method which not only draws the essence of other countries, but also accords with the situation of the own country and has the characteristics of independence, objectivity, continuity, non-profit, authority and the like is a great urgency in the China broadcast television industry.
The invention content is as follows:
the invention mainly aims to collect multi-screen behavior data of intelligent terminal users such as DVB two-way terminals, IPTV, OTT, intelligent televisions, mobile phones, tablet computers and the like through the information return advantages of two-way networks and the Internet in the face of more and more flexible two-way new media services, and combines the time data, channel data, program data, advertisement data and other basic information data, through HDFS distributed storage, ETL extraction, conversion and loading, an algorithm processing module and a multi-dimensional analysis module are utilized to carry out multi-dimensional analysis on massive multi-screen user behavior data, and through analyzing the behavior trend of users, in the aspect of setting evaluation indexes, the audience rating, the satisfaction (or audience review) and the expert review are multiplied by different difficulty coefficients to obtain a comprehensive examination score, and then a whole set of program evaluation method based on new media multi-source cross-screen data analysis is formed. The comprehensive judgment of objective data and subjective evaluation is provided for program evaluation.
The specific technical scheme of the invention is as follows:
a program evaluation method based on new media multisource cross-screen data analysis comprises the steps of firstly returning the information of the bidirectional network and the internet to the superiority, collecting the multi-screen behavior data of intelligent terminal users such as DVB bidirectional terminals, IPTV, OTT, intelligent televisions, mobile phones, tablet computers and the like, and combines the time data, channel data, program data, advertisement data and other basic information data with the user chat data, television data, forum postings, search records, website access and other non-video behavior data acquired by a third-party acquisition system, the HDFS distributed storage module is used for carrying out three-backup distributed storage, the ETL module is used for extracting, converting and loading mass behavior data, and then the algorithm processing module carries out data preprocessing operation on the converted mass behavior data through an algorithm package and a data model which are optimized and combined.
In the scheme, the method effectively supplements the viewing data of the programs by using the broadcasting platform data and indexes except for the live broadcast channel, comprehensively evaluates and assesses the spreading value of the programs, and provides data reference for the market operation of the programs except for the live broadcast.
In the scheme, the method comprises television user viewing behavior analysis, internet video user behavior analysis, mobile user behavior analysis and internet public opinion analysis. Under the condition that all data sources are communicated by the multi-screen technology, multi-screen data and public opinion monitoring conditions are fused to evaluate the value of a program.
In the above scheme, the internet video user behavior analysis is based on statistics and analysis of basic data of a video content website, and is different from the concept of a traditional network analysis tool PV and UV, and the statistics includes: effective playing times, average playing time and other basic operation data.
In the scheme, the Internet public opinion analysis comprises audience gender, audience type, audience regional distribution and audience voice.
The method has the following beneficial effects:
1) for a television platform, the method integrates data resources of DVB, IPTV and OTT multi-play into an index of a uniform caliber, and is not the only evaluation for the DVB television platform in the past.
2) By the method, the information return advantages of a two-way network of an operator and the Internet can be utilized, massive multi-screen behavior data of users can be obtained with the most economic investment, objective viewing data of programs watched by the users at a television terminal and a mobile terminal can be analyzed quickly, effectively and accurately, and the method is not limited to a television platform.
3) The audience rating does not represent the satisfaction degree, so the method combines objective audience rating and subjective cognition, and constructs a multi-source and perfect multi-screen program evaluation system.
Description of the drawings:
the invention is further described below in conjunction with the appended drawings and the detailed description.
Fig. 1 is a block diagram of multi-source viewership data analysis in accordance with the present invention.
Fig. 2 is a block diagram of such a multi-source program evaluation architecture in accordance with the present invention.
The specific implementation mode is as follows:
in order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further explained below by combining the specific drawings.
The invention relates to a program evaluation method based on new media multisource cross-screen data analysis, which comprises the steps of firstly returning the information of a bidirectional network and the internet to the superiority, acquiring the multi-screen behavior data of intelligent terminal users such as DVB bidirectional terminals, IPTV, OTT, intelligent televisions, mobile phones, tablet computers and the like, and combines the time data, channel data, program data, advertisement data and other basic information data with the user chat data, television data, forum postings, search records, website access and other non-video behavior data acquired by a third-party acquisition system, the HDFS distributed storage module is used for carrying out three-backup distributed storage, the ETL module is used for extracting, converting and loading mass behavior data, and then the algorithm processing module carries out data preprocessing operation on the converted mass behavior data through an algorithm package and a data model which are optimized and combined.
On one hand, the multi-source data firstly considers the data aggregation of a television large screen, and the evaluation is carried out by fusing DVB, IPTV and OTT data (such as figure 1 and figure 2); on the other hand, with the rapid development of the digitization process and new media, the electronic screen transmission begins to extend to the digital video field, the attention of audiences is distributed from the traditional television to the internet and mobile terminals, and the media is not the age with the unique audience rating. Audience can watch television programs of the same resource through various channels, and under the diversity of social media, the audience rating conditions of the programs broadcasted in various forms and a series of behaviors such as spreading and public sentiment under the socialization become a new measuring standard.
The multi-source program evaluation system can effectively supplement the viewing data of the programs by using the broadcasting platform data and indexes except for the live broadcast channels, comprehensively evaluate and assess the spreading value of the programs and provide data reference for the market operation of the programs except for the live broadcast.
The multi-source program evaluation system comprises television user viewing behavior analysis, internet video user behavior analysis, mobile user behavior analysis and internet public opinion analysis. Under the condition that all data sources are communicated by the multi-screen technology, multi-screen data and public opinion monitoring conditions are fused to evaluate the value of a program.
1. Internet video user behavior analysis
Based on the statistics and analysis of the basic data of the video content website, the statistics is different from the concept of the traditional network analysis tool PV, UV, and the statistics comprises the following steps: effective playing times, average playing time and other basic operation data. The data is combined with the television viewing data to judge the viewing condition, the adhesion degree and the like of the programs in the network media broadcasting environment.
2. Internet public opinion analysis
Besides objective viewing data, public sentiment effects brought by the internet are also receiving more and more attention. The weather chart like the program has the subjective idea of personal emotional colors, and the interactive form of the weather chart more intuitively reflects the preference of audiences.
Audience gender: audience gender distribution for participating in program discussions.
Audience type: audience authentication types that participate in the program discussion, such as general users, senior dawns, celebrities, and the like.
Audience regional distribution: the subject geographical distribution participating in the program discussion.
Audience voice: specific topics discussed by the audience are examples of ratings for programs, keywords, people mentioned in the discussion, brands, etc.
In summary, the method of the present invention utilizes the information return advantages of the operator's two-way network and the internet to obtain a great amount of multi-screen behavior data of the user with the most economic investment, and quickly, effectively and accurately analyze the user attribute information to obtain the personnel profile and the behavior trend of the user. Meanwhile, data support and accurate positioning can be provided for putting and transmitting services, advertisements and information in real time according to the user personnel outline and the behavior trend obtained through analysis, the putting effect and the transmitting effect of the services, the advertisements and the information are improved, and the obtained benefits are maximized. The survey difficulty and the survey cost of mass user attributes are greatly reduced.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed.
Claims (5)
1. A program evaluation method based on new media multisource cross-screen data analysis is characterized by firstly collecting multiscreen behavior data of intelligent terminal users such as DVB (digital video broadcasting) bidirectional terminals, IPTV (Internet protocol television), OTT (over the top of the bottom.
2. The program evaluation method based on new media multi-source cross-screen data analysis as claimed in claim 1, wherein the method utilizes the broadcasting platform data and indexes except for the live channel to effectively supplement the program viewing data, comprehensively evaluate the spreading value of the assessment program, and provide data reference for the market operation of the program except for live television.
3. The program evaluation method based on new media multi-source cross-screen data analysis as claimed in claim 1, wherein the method comprises television user viewing behavior analysis, internet video user behavior analysis, mobile user behavior analysis and internet public opinion analysis; under the condition that all data sources are communicated by the multi-screen technology, multi-screen data and public opinion monitoring conditions are fused to evaluate the value of a program.
4. The program evaluation method based on new media multi-source cross-screen data analysis of claim 3, wherein the internet video user behavior analysis is based on statistics and analysis of basic data of video content websites, which is different from the concept of conventional network analysis tools PV, UV, and the statistics includes: effective playing times, average playing time and other basic operation data.
5. The program assessment method based on new media multi-source cross-screen data analysis of claim 3, wherein the internet public opinion analysis comprises audience gender, audience type, audience geographic distribution and audience voice.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112070614A (en) * | 2020-08-13 | 2020-12-11 | 华数传媒网络有限公司 | Asset value evaluation model and method based on all media |
| CN113158066A (en) * | 2021-05-11 | 2021-07-23 | 两比特(北京)科技有限公司 | Cloud data movie and television play effect analysis system |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2001052173A1 (en) * | 2000-01-13 | 2001-07-19 | Erinmedia, Inc. | Privacy compliant multiple dataset correlation system |
| CN104516983A (en) * | 2015-01-08 | 2015-04-15 | 龙思薇 | Data display method |
| CN105302831A (en) * | 2014-07-18 | 2016-02-03 | 上海星红桉数据科技有限公司 | High-speed calculation analysis method based on mass user behavior data |
| CN105323601A (en) * | 2014-07-18 | 2016-02-10 | 上海星红桉数据科技有限公司 | Personnel attribute identification method based on multi-screen user behavior data |
| CN105872624A (en) * | 2015-12-14 | 2016-08-17 | 乐视网信息技术（北京）股份有限公司 | Audience rating statistic method, terminal, server and system |
| CN105898409A (en) * | 2014-10-16 | 2016-08-24 | 中国传媒大学 | Big data based cross-platform television program evaluation system |
| CN106375796A (en) * | 2016-09-08 | 2017-02-01 | 深圳市茁壮网络股份有限公司 | Audience rating statistical method and system |
-
2018
- 2018-06-22 CN CN201810666203.2A patent/CN110636344A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2001052173A1 (en) * | 2000-01-13 | 2001-07-19 | Erinmedia, Inc. | Privacy compliant multiple dataset correlation system |
| CN105302831A (en) * | 2014-07-18 | 2016-02-03 | 上海星红桉数据科技有限公司 | High-speed calculation analysis method based on mass user behavior data |
| CN105323601A (en) * | 2014-07-18 | 2016-02-10 | 上海星红桉数据科技有限公司 | Personnel attribute identification method based on multi-screen user behavior data |
| CN105898409A (en) * | 2014-10-16 | 2016-08-24 | 中国传媒大学 | Big data based cross-platform television program evaluation system |
| CN104516983A (en) * | 2015-01-08 | 2015-04-15 | 龙思薇 | Data display method |
| CN105872624A (en) * | 2015-12-14 | 2016-08-17 | 乐视网信息技术（北京）股份有限公司 | Audience rating statistic method, terminal, server and system |
| CN106375796A (en) * | 2016-09-08 | 2017-02-01 | 深圳市茁壮网络股份有限公司 | Audience rating statistical method and system |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112070614A (en) * | 2020-08-13 | 2020-12-11 | 华数传媒网络有限公司 | Asset value evaluation model and method based on all media |
| CN113158066A (en) * | 2021-05-11 | 2021-07-23 | 两比特(北京)科技有限公司 | Cloud data movie and television play effect analysis system |
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Application publication date: 20191231 |