News propagation optimization method and system based on new media technology

Abstract

The invention discloses a new media technology-based news transmission optimization method and system, and belongs to the technical field of news transmission, and the system comprises an application identification module, an application analysis module, a news calibration module and a release optimization module; the application identification module is used for carrying out real-time analysis on the reference news mode to obtain a news detail graph, and the application analysis module is used for carrying out real-time analysis on the news detail graph to obtain a recommendation optimization mode of a corresponding news node in the news detail graph; the news calibration module is used for carrying out calibration analysis on the news content and carrying out corresponding processing on the corresponding news content according to a content calibration result; the publishing optimization module is used for optimizing publishing of the news content and determining target news according to a content calibration result; performing release retrieval according to the target news to obtain a plurality of pieces of reference news, screening the reference news to obtain released reference news, and identifying release information of the released reference news; and performing supplementary publishing processing on the target news according to the publishing information.

Description

Technical Field

[0001] The present invention belongs to the technical field of news dissemination, and specifically relates to a news dissemination optimization method and system based on new media technology. Background Art

[0002] In recent years, new media technologies have profoundly changed the technical landscape and application model of news dissemination. Technologies such as artificial intelligence, big data, and blockchain have gradually penetrated into news production, distribution, and interaction, significantly improving dissemination efficiency and credibility.

[0003] However, there are still significant technical contradictions and efficiency shortcomings in the current news communication field. For example, there is an imbalance between communication efficiency and credibility. The algorithm recommendation mechanism has spawned an "traffic first" ecology. Some media fabricate false information to gain popularity. Due to the algorithm mechanism, the forwarded and adapted news lacks credibility, which affects the credibility of the subject. After the news is issued, there is no positive feedback, resulting in a gradual decrease in the audience. In addition, the production of news content is hollowed out. Through the assembly line production model of "general draft + adaptation", the narrative and folk cognition are misaligned, which continues to consume the credibility of the media.

[0004] Based on this, in order to solve the drawbacks of existing news dissemination, the present invention provides a news dissemination optimization method and system based on new media technology. Summary of the invention

[0005] In order to solve the problems existing in the above-mentioned scheme, the present invention provides a news dissemination optimization method and system based on new media technology.

[0006] The purpose of the present invention can be achieved through the following technical solutions: A news dissemination optimization system based on new media technology, including an application identification module, an application analysis module, a news calibration module and a release optimization module; The application identification module is used to perform real-time analysis on the benchmark news mode to obtain a news detail graph of the benchmark news mode, where the benchmark news mode is the news flow mode of the current application; the news detail graph is composed of news nodes and node features of corresponding news nodes.

[0007] Furthermore, real-time analysis of benchmark news methods is performed, including: Identify corresponding news nodes according to the benchmark news mode, determine the order relationship between each news node, and generate a node flow chart according to the order relationship between each news node; According to the news node, the benchmark news mode is subjected to real-time feature recognition to obtain node features corresponding to the news node; the node features are added to a node flow chart, and the added node flow chart is marked as a news detail chart.

[0008] The application analysis module is used to perform real-time analysis on the news detailed map, obtain the recommended optimization methods for the corresponding news nodes in the news detailed map, obtain the recommended optimization information of the recommended optimization methods, and display the recommended optimization information to the user.

[0009] Further, the real-time analysis of the news detailed map includes: The platform party establishes a new media technology library and updates it in real time; the new media technology library is used to store various intelligent technology information applied to the news process and the technical feature data of the corresponding intelligent technologies; Identify the node features of each news node in the news detail map, perform technology matching in the new media technology library according to the node features, and obtain the intelligent technology information applicable to the news node; obtain the corresponding technical feature data according to the intelligent technology information, and determine the performance value and adaptation value of the intelligent technology according to the technical feature data; calculate the first optimization value of the intelligent technology according to the first optimization formula, and the first optimization formula is: YA = b1×XZ + b2×SZ; In the formula: YA is the first optimization value; b1 and b2 are both proportionality coefficients, and the value range is 0 < b1 ≤ 1, 0 < b2 ≤ 1; XZ is the performance value; SZ is the adaptation value; Judge whether the intelligent technology meets the recommended optimization requirements according to the first optimization value, and obtain the recommended judgment result of the intelligent technology; mark the intelligent technology with the recommended judgment result that meets the recommended optimization requirements as the recommended optimization method.

[0010] Further, record the recommended judgment results of each intelligent technology in real time, and screen the matched intelligent technologies according to the recommended judgment results when performing technology matching according to the node features.

[0011] The news calibration module is used to perform calibration analysis on the news content, obtain the content calibration result of the corresponding news content, and the content calibration result includes authenticity anomaly, content hollowing, and normal content verification; perform corresponding processing on the corresponding news content according to the content calibration result.

[0012] Further, the calibration analysis of the news content includes: The platform party establishes a feature recognition library, and the feature recognition library is used to store abnormal feature groups and the abnormal probabilities corresponding to the abnormal feature groups. The abnormal feature groups are news feature combinations corresponding to authenticity anomalies or content hollowing; Establish a content calibration model according to the feature recognition library, and the expression of the content calibration model is: ; Where: NS is the news content, the output data is the content calibration value NP (NS), and the content calibration value is 1, 2 or 0; if the first calibration standard is met, it means that the content calibration result of the corresponding news content is content hollowing; if the second calibration standard is met, it means that the content calibration result of the corresponding news content is authenticity abnormal; The news content is analyzed by a content calibration model to obtain a content calibration value of the news content, and a content calibration result of the news content is determined according to the content calibration value.

[0013] Furthermore, when the content calibration result of the news content is abnormal in authenticity, the news content is converted into a false certificate according to a preset method to obtain news conversion content, and the news conversion content, news content and content calibration result are displayed to the user.

[0014] The publishing optimization module is used to optimize the publishing of news content, identify the content calibration results of the news content in real time, and mark the news content whose content calibration results are not normal as target news; A release search is performed according to the target news to obtain a number of reference news related to the target news, the reference news is screened to obtain release reference news, and release information of the release reference news is identified; and a supplementary release process is performed on the target news according to the release information.

[0015] Furthermore, the reference news is screened, including: Deduplication is performed on the reference news, and the deduplication reference news is analyzed through a content calibration model to obtain a content calibration result of the reference news; the reference news whose content calibration result is normal is deleted; and the remaining reference news is marked as published reference news.

[0016] Furthermore, the release information of the reference news is optimized and adjusted.

[0017] Furthermore, the published information is optimized and adjusted, including: Identify the publisher corresponding to the published information, and obtain the news optimization features of the publisher; establish a publishing optimization model, and the expression of the publishing optimization model is: ; Where: YT i represents the news optimization feature of the publisher corresponding to the published information, i=1, 2, ..., n, n is the number of publishers corresponding to the published information; the output data is the publication optimization value PR (YT i ), publish optimization value is 1 or 0; The news optimization features are analyzed according to a publishing optimization model to obtain a publishing optimization value of the publisher; and the publishing information is optimized and adjusted according to the publishing optimization value.

[0018] A news dissemination optimization method based on new media technology, the method comprising: Conduct real-time analysis on the benchmark news mode to obtain news details of the benchmark news mode; Perform real-time analysis on the news detailed graph, obtain recommended optimization methods for corresponding news nodes in the news detailed graph, obtain recommended optimization information of the recommended optimization methods, and display the recommended optimization information to users; Perform calibration analysis on news content to obtain content calibration results of corresponding news content, and perform corresponding processing on corresponding news content according to the content calibration results; Mark the news content that is not normal in the content calibration result as the target news; perform release retrieval based on the target news to obtain a number of reference news related to the target news, screen the reference news, obtain the release reference news, and identify the release information of the release reference news; perform supplementary release processing on the target news based on the release information.

[0019] Compared with the prior art, the present invention has the following beneficial effects: Through the mutual cooperation among the application identification module, application analysis module, news calibration module and release optimization module, dynamic optimization of news dissemination based on new media technology is achieved; the optimized news dissemination method can locate the target audience more accurately, thereby expanding the coverage of news and enabling more potential readers to access relevant information; by solving the problems of news hollowing out and reduced credibility; and at the same time, supplementary optimization processing of news release is carried out based on the content calibration results, so as to carry out news dissemination in a more targeted manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0022] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] like Figure 1 As shown, a news dissemination optimization system based on new media technology includes an application identification module, an application analysis module, a news calibration module and a release optimization module; The application identification module is used to analyze the current news flow mode, mark the news flow mode of the current application as the benchmark news mode, and set it according to the user's news optimization needs, such as the whole process from news generation to distribution; identify news nodes according to the benchmark news mode, such as information collection and topic selection, news production, content review, content distribution and other news nodes, and determine them specifically in combination with the actual news flow at the user; generate a node flow chart according to the benchmark news mode and the news nodes, that is, determine the order relationship of each news node according to the benchmark news mode, and then generate a node flow chart according to the order relationship and the news nodes; According to the node flow chart, the benchmark news mode is identified in real time to obtain the node features of the corresponding news node. The node features are identified according to the actual application method of the news node, such as information collection and topic selection, which can be obtained through various methods such as on-site reporter interviews and network collection; the node features are added to the node flow chart to form a news details map.

[0024] The application analysis module is used to perform real-time analysis on the news detailed graph, determine the recommended optimization method for the corresponding news node, obtain recommended optimization information of the recommended optimization method, and display the recommended optimization information to the user. The user then decides whether to perform optimization adjustments according to the recommended optimization method.

[0025] In one embodiment, the news detailed graph is analyzed in real time, including: The platform party establishes a new media technology library according to the development of new media technologies. The new media technology library is used to store various intelligent technology information that can be applied to the news process, such as various relevant intelligent technologies corresponding to artificial intelligence, big data, blockchain, 5G communication technology, virtual reality, etc.; Exemplarily, big data technology can analyze user behavior, build portraits, and achieve precise push; Artificial intelligence helps with automated production and personalized recommendation; Blockchain technology ensures the authenticity of news and the traceability of sources; 5G technology accelerates content transmission and supports high-definition multimedia live broadcast; Virtual reality and augmented reality can create immersive news experiences; The intelligent technology information is the introduction data of the corresponding intelligent technology, such as relevant data like technology name, advantages, application directions, etc. For the same intelligent technology, different technologies will be formed according to the differences in application methods. For example, artificial intelligence is just a general concept, and the actual intelligent technologies formed are diverse.

[0026] Analyze the intelligent technologies corresponding to each intelligent technology information in the new media technology library, determine the performance values corresponding to each news node within the applicable range of the corresponding intelligent technology and the adaptation values with other various news node application technologies, and integrate them into the technical feature data of the intelligent technology. Both the performance value and the adaptation value use the same percentage value or decimal value, etc. Specify the performance values and adaptation values corresponding to the best and worst cases of the corresponding news nodes respectively. Subsequently, set several reference standards and the corresponding performance values and adaptation values in the middle. Subsequently, match the performance values and adaptation values according to actual applications. The performance value is set according to the application effect of the intelligent technology, and the adaptation value is set according to the overall adaptation situation of the intelligent technology; Generally, when determining the intelligent technology, the staff set the technical feature data, which can be set by means of actual simulation verification, experimental data summary, etc.; It is also possible to establish an intelligent model based on intelligent technologies such as deep learning algorithms to intelligently extract technical adjustment data; Store the technical feature data in the new media technology library; And dynamically update the new media technology library according to technological development.

[0027] Identify the node features of each news node in the news details map, perform technology matching in the new media technology library according to the node features, and obtain the intelligent technology information applicable to the news node; Obtain the corresponding technical feature data according to the intelligent technology information, and determine the performance value and adaptation value corresponding to the intelligent technology according to the technical feature data; Calculate the first optimization value of the corresponding intelligent technology according to the first optimization formula. The first optimization formula is: YA = b1×XZ + b2×SZ; In the formula: YA is the first optimization value; b1 and b2 are both proportionality coefficients, and the value range is 0 < b1 ≤ 1, 0 < b2 ≤ 1; XZ is the performance value; SZ is the adaptation value; Determine the first optimization value of the application technology of each news node in the news detailed graph according to the calculation method of the first optimization value, and mark it as the node application value. The node application value of each news node can be synchronously determined by the platform when establishing the news detailed graph, or the node application value can be determined by other methods; compare the first optimization value with the node application value of the corresponding news node to determine whether the corresponding intelligent technology meets the optimization recommendation requirements, such as being only greater than the node application value, being greater than a preset difference compared with the node application value, etc., to obtain a corresponding recommendation judgment result; mark the corresponding intelligent technology as a recommended optimization method according to the recommendation judgment result, and set the recommended optimization information according to the corresponding intelligent technology information and the first optimization value, so as to display the corresponding recommended optimization method in detail to the user.

[0028] In one embodiment, the recommendation and judgment results of each intelligent technology are recorded in real time, and the matching intelligent technology is screened when the technology is matched according to the node characteristics based on the recommendation and judgment results; that is, the recorded intelligent technology that will not be used as the current news node is screened to improve data analysis efficiency.

[0029] The news calibration module is used to perform calibration analysis on news content to obtain content calibration results of corresponding news content, which include authenticity anomalies, content hollowing out and normal content verification; the corresponding news content is processed accordingly according to the content calibration results; for example, the news content can be readjusted for content hollowing out, and an early warning can be issued for authenticity anomalies. After confirming false information, news is reversely generated to inform the public of the false information, and the processing is specifically performed according to the preset processing methods of different content calibration results.

[0030] In one embodiment, the news content is calibrated and analyzed based on existing calibration methods, such as using a deep learning algorithm to establish an intelligent calibration model, and manually establishing a corresponding training set for training. The training set includes input data and output data. The input data is news content-related information, including news content, content source, and other information related to the generation of the news content, which is mainly used to analyze its authenticity; the output data is the content calibration result, and the calibration analysis is performed based on the intelligent calibration model after successful training to obtain the corresponding content calibration result.

[0031] In one embodiment, the news content is subjected to calibration analysis, including: Based on big data and other technologies, statistics are collected on abnormal feature groups and abnormal probabilities corresponding to hollow news and false news content, that is, which feature components may indicate hollow news or false news content, and the probability that the abnormal feature combination is the corresponding hollow news or false news content, and statistics are made based on the share ratio; corresponding authenticity abnormal labels or hollow content labels are marked for abnormal feature groups; after integrating the obtained abnormal feature groups and abnormal probabilities, a feature recognition library is established, and the feature recognition library is dynamically updated; A content calibration model is established based on the feature recognition library. The content calibration model is used to analyze the news content based on the feature recognition library, perform feature matching on the news content based on the feature recognition library, and determine whether the news content has a matching abnormal feature group. If there is no matching abnormal feature group, the content calibration result is that the content verification is normal. If there is an abnormal feature group, the corresponding abnormal probability is identified, and it is determined whether the content verification is normal, the authenticity is abnormal, or the content is hollowed out according to the abnormal probability; training is performed using the set training set, and learning and adjustment are performed in combination with the subsequent manual verification results based on the content calibration results. The main adjustment is the corresponding verification standard, which is divided into the first verification standard and the second verification standard. If the first verification standard is met, it means that the content is hollowed out; if the second verification standard is met, it means that the authenticity is abnormal; the expression of the content calibration model is: ; Where: NS is the input data, i.e. the news content, and the output data is the content check value NP (NS), which is 1, 2 or 0. Because the news content can meet both the first check standard and the second check standard, a news content can have two content check values. The news content is analyzed through the content calibration model to obtain the content calibration value of the corresponding news content, and the content calibration result of the news content is determined according to the content calibration value.

[0032] In one embodiment, when the content calibration result of the news content is abnormal in authenticity, the corresponding news content is converted into a false certificate according to a preset conversion method to obtain new news content, and the new news content is marked as news conversion content. The news conversion content, news content and content calibration result are displayed to the user, and the user performs manual confirmation and calibration later.

[0033] The conversion method is to convert the news content in a direction that indicates that it is false information. For the method of intelligent news generation, the conversion can be carried out according to the corresponding news generation method; or an intelligent model can be established based on existing intelligent algorithms to convert news content, such as establishing an intelligent model based on a CNN network or a DNN network, and manually establishing a corresponding training set for training. The training set includes input data and output data. The input data is news content-related data, such as news content, content source and other related data, and the output data is news conversion content. The intelligent model after successful training is used for conversion analysis to form a preset conversion method.

[0034] The release optimization module is used to optimize the release of news content, which refers to news content that has undergone multiple processes such as verification and is waiting to be released; the news content that has been processed as authenticity anomaly or content hollowing out according to the content calibration result is marked as target news, that is, the target news includes news content that has been processed due to content hollowing out or authenticity anomaly, including news content that has been deleted, adjusted, and other processing measures. For the deleted processing, the original news content is used as the target news; for other news content, it is released according to the preset release method, mainly optimizing the release of the target news, because the target news has a more directional release background.

[0035] According to the target news, a release search is performed to obtain several reference news related to the target news, such as those related to the original news content, the processed news content, etc., including false and hollow related news of the target news, and also including related news that is equivalent to the target news; the reference news is deduplicated, that is, only one identical reference news is included, but the corresponding release information of the reference news is recorded, that is, which release entities have released it, to form the release information of each reference news.

[0036] The reference news is analyzed according to the content calibration model to obtain the content calibration results of the corresponding reference news, and the reference news with the content calibration results showing that the content is normal is deleted; and the remaining reference news is marked as published reference news.

[0037] Identify the release information of the reference news, and perform supplementary release processing on the target news according to the release information; specifically perform supplementary release processing according to the user's release needs, such as making associated supplementary releases in the release channels corresponding to the corresponding publishers, directly publishing under the publisher's news, identifying the viewers of the corresponding reference news, and publishing according to the composition of the corresponding viewers, etc. Specifically, there are multiple ways to perform supplementary release processing based on clear publishers and reference news.

[0038] In one embodiment, in order to improve resource utilization, the release information of the corresponding release reference information is analyzed to determine whether it meets the requirements for supplementary release processing, mainly based on the number of news views, number of comments, news popularity, etc., and publishers who do not meet the requirements are removed from the release information to achieve optimization of the release information.

[0039] In one embodiment, the published information can be optimized and adjusted based on existing methods, such as establishing an intelligent model based on a neural network, and manually establishing a corresponding training set for training. The training set includes input data and output data. The input data is the news optimization features corresponding to the corresponding publisher in the published information, which are mainly related to the news views, number of comments, news popularity, etc. The output data is whether the corresponding publisher meets the supplementary release processing requirements. The intelligent model after successful training is used for analysis to optimize the published information.

[0040] In one embodiment, optimizing and adjusting the published information includes: Identify the publisher corresponding to the published information, and obtain the news optimization features corresponding to the corresponding publisher; establish a publishing optimization model, set up a training set for training based on relevant historical data or manual settings, and the training set includes input data and output data. The input data is the news optimization features, and the output data is whether the corresponding publisher meets the supplementary publishing processing requirements; the expression of the publishing optimization model is: ; Where: YT i represents the news optimization feature of the publisher corresponding to the published information, i=1, 2, ..., n, n is the number of publishers corresponding to the published information; the output data is the publication optimization value PR (YT i ), publish optimization value is 1 or 0; The news optimization features are analyzed according to the publishing optimization model to obtain the publishing optimization value of the corresponding publisher; the publishing information is optimized and adjusted according to the publishing optimization value, and the publisher information with a publishing optimization value of 0 is eliminated.

[0041] A news dissemination optimization method based on new media technology, the method comprising: Conduct real-time analysis on the benchmark news mode to obtain news details of the benchmark news mode; Perform real-time analysis on the news detailed graph, obtain recommended optimization methods for corresponding news nodes in the news detailed graph, obtain recommended optimization information of the recommended optimization methods, and display the recommended optimization information to users; Perform calibration analysis on news content to obtain content calibration results of corresponding news content, and perform corresponding processing on corresponding news content according to the content calibration results; Mark the news content that is not normal in the content calibration result as the target news; perform release retrieval based on the target news to obtain a number of reference news related to the target news, screen the reference news, obtain the release reference news, and identify the release information of the release reference news; perform supplementary release processing on the target news based on the release information.

[0042] The above formulas are all calculated by removing dimensions and taking numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data.

[0043] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A news dissemination optimization system based on new media technology, characterized in that: It includes an application recognition module, an application analysis module, a news calibration module, and a release optimization module; The application recognition module is used to perform real-time analysis on the benchmark news mode to obtain a news detail map of the benchmark news mode, where the benchmark news mode is the news process mode of the current application; the news detail map consists of news nodes and the node features of the corresponding news nodes; The application analysis module is used to perform real-time analysis on the news detail map to obtain the recommended optimization method for the corresponding news nodes in the news detail map, obtain the recommended optimization information of the recommended optimization method, and display the recommended optimization information to the user; The news calibration module is used to perform calibration analysis on the news content to obtain the content calibration result of the corresponding news content, and the content calibration result includes authenticity anomaly, content hollowing, and normal content verification; Perform corresponding processing on the corresponding news content according to the content calibration result; The release optimization module is used to perform optimization processing on the release of the news content, real-time identify the content calibration result of the news content, and mark the news content with a content calibration result other than normal content verification as the target news; Perform a release search based on the target news to obtain several reference news related to the target news, screen the reference news to obtain the release reference news, and identify the release information of the release reference news; perform supplementary release processing on the target news according to the release information.

2. According to claim 1, a news dissemination optimization system based on new media technology is characterized in that: Performing real-time analysis on the benchmark news mode includes: Identifying the corresponding news nodes according to the benchmark news mode, determining the sequential relationship between each news node, and generating a node flow chart according to the sequential relationship between each news node; Performing real-time feature recognition on the benchmark news mode according to the news nodes to obtain the node features corresponding to the news nodes; supplementing the node features into the node flow chart, and marking the supplemented node flow chart as the news detail map.

3. According to claim 1, a news dissemination optimization system based on new media technology is characterized in that: Performing real-time analysis on the news detail map includes: The platform party establishes a new media technology library and updates it in real time; the new media technology library is used to store various intelligent technology information applied to the news process and the technical feature data of the corresponding intelligent technology; Identifying the node features of each news node in the news detail map, performing technology matching in the new media technology library according to the node features to obtain the intelligent technology information applicable to the news node; obtaining the corresponding technical feature data according to the intelligent technology information, and determining the performance value and adaptation value of the intelligent technology according to the technical feature data; calculating the first optimization value of the intelligent technology according to the first optimization formula, and the first optimization formula is: YA = b1×XZ + b2×SZ; In the formula: YA is the first optimization value; b1 and b2 are both proportionality coefficients, and the value range is 0 < b1 ≤ 1, 0 < b2 ≤ 1; XZ is the performance value; SZ is the adaptation value; Judging whether the intelligent technology meets the recommended optimization requirements according to the first optimization value to obtain the recommended judgment result of the intelligent technology; marking the intelligent technology with a recommended judgment result that meets the recommended optimization requirements as the recommended optimization method.

4. According to claim 3, a news dissemination optimization system based on new media technology is characterized in that: The recommended judgment results of each intelligent technology are recorded in real time, and the matching intelligent technology is screened when the technology is matched according to the node characteristics according to the recommended judgment results.

5. According to the news dissemination optimization system based on new media technology as described in claim 1, it is characterized in that: Conduct calibrated analysis of news content, including: The platform establishes a feature recognition library, which is used to store abnormal feature groups and abnormal probabilities corresponding to the abnormal feature groups. The abnormal feature groups are news feature combinations corresponding to authenticity anomalies or hollow content. A content calibration model is established based on the feature recognition library. The expression of the content calibration model is: ； Where: NS is the news content, the output data is the content calibration value NP (NS), and the content calibration value is 1, 2 or 0; if the first calibration standard is met, it means that the content calibration result of the corresponding news content is content hollowing; if the second calibration standard is met, it means that the content calibration result of the corresponding news content is authenticity abnormal; The news content is analyzed by a content calibration model to obtain a content calibration value of the news content, and a content calibration result of the news content is determined according to the content calibration value.

6. A news dissemination optimization system based on new media technology according to claim 5, characterized in that: When the content calibration result of the news content is abnormal in authenticity, the news content is converted into a false certificate according to the preset method to obtain news conversion content, and the news conversion content, news content and content calibration result are displayed to the user.

7. The news dissemination optimization system based on new media technology according to claim 1 is characterized in that: Filter the reference news, including: Deduplication is performed on the reference news, and the deduplication reference news is analyzed through a content calibration model to obtain a content calibration result of the reference news; the reference news whose content calibration result is normal is deleted; and the remaining reference news is marked as published reference news.

8. The news dissemination optimization system based on new media technology according to claim 1 is characterized in that: Optimize and adjust the release information of reference news.

9. The news dissemination optimization system based on new media technology according to claim 8 is characterized in that: Optimize and adjust the published information, including: Identify the publisher corresponding to the published information, and obtain the news optimization features of the publisher; establish a publishing optimization model, and the expression of the publishing optimization model is: ； Where: YT i represents the news optimization feature of the publisher corresponding to the published information, i=1, 2, ..., n, n is the number of publishers corresponding to the published information; the output data is the publication optimization value PR (YT i ), publish optimization value is 1 or 0; The news optimization features are analyzed according to a publishing optimization model to obtain a publishing optimization value of the publisher; and the publishing information is optimized and adjusted according to the publishing optimization value.

10. A news dissemination optimization method based on new media technology, characterized in that: A news dissemination optimization system based on new media technology as applied to any one of claims 1 to 9, the method comprising: Conduct real-time analysis on the benchmark news mode to obtain news details of the benchmark news mode; Perform real-time analysis on the news detailed graph, obtain recommended optimization methods for corresponding news nodes in the news detailed graph, obtain recommended optimization information of the recommended optimization methods, and display the recommended optimization information to users; Perform calibration analysis on news content to obtain content calibration results of corresponding news content, and perform corresponding processing on corresponding news content according to the content calibration results; Mark the news content that is not normal in the content calibration result as the target news; perform release retrieval based on the target news to obtain a number of reference news related to the target news, screen the reference news, obtain the release reference news, and identify the release information of the release reference news; perform supplementary release processing on the target news based on the release information.

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