Abstract
With the development of technology and the traditional newspaper industry’s emphasis on technological dividends, news reporting will open up a larger market in the future. Since the deep trust network mode was proposed, news reports will have more room for changes in the future. Although we still have to insist that content is king, we cannot give up technology, let alone ignore the times. It is necessary to understand the importance and arduousness of the task of innovation in current affairs news reports, and to be firm in the new era, innovation in current affairs news reports lies in the core of voice. The article mainly puts forward the research questions and purposes and collects the literature of contemporary political news communication, the context of new media, and new news communication methods. This paper analyzes the application of deep trust network model in news communication and explained the content, research methodology, and innovation points. It focuses on the ecological background of local news and current affairs dissemination in the context of new media and highlights the impact and challenge activities of new media topics that combine today’s news coverage. Through case analysis, this article will analyze the present way of presenting news communication activities from four aspects: “content innovation,” “form innovation,” “means innovation,” and “communication power innovation.” The results showed that 43% of the respondents chose “primarily online reading” and 21% of the respondents chose “new reading tastes.” 14% of the respondents chose “reading with less paper,” and 11% of the respondents chose “mobile phone as one of the reading devices.”
1. Introduction
In today’s world, Internet technology is advancing, people’s life and entertainment methods are also undergoing major changes, and hot spots and major events have attracted attention. Some intelligent communication media such as artificial intelligence devices, media, and virtual reality technology are slowly changing the way people see and think about news. Due to the influence of media intelligence, traditional news disseminators have to make corresponding plans and changes. Especially in the context of media convergence, the updating and upgrading of news production tools such as some news clients also involve changes in the main body of news dissemination.
Experts at home and abroad have also produced many research results on the deep trust network model and news dissemination in the micromedia era. Daniela et al. want news organizations to be open about how their applications analyze and process news. These requirements are embodied in the Washington State Department of Transportation’s Performance Journalism Principles [1]. Koljonen can assert that the psychological state of journalists has fundamentally changed in recent decades. Journalism as early as the 1970s and 1980s was still committed to the core values of “highly modern” [2]. The results of Krieken and Sanders’ research show that in public discourse about narrative news, news that reflects social manifestations is framed as moving, basic, and high-quality news [3]. Martin believes that in the digital age, the practice of journalism itself has changed. Stories are generated by many participants in an engaging and interactive way [4]. Young et al.’s research examines the quality of winners and finalists of major national and international data journalism awards. As early as 2012, a content analysis of data projects submitted by Canadian media to three press associations was completed [5]. Carlson’s research treats controversial responses as meta-journalistic discourses. He talks about journalism aimed at defining proper practice and legal form [6]. Taking Schudson’s seminal work in the historical sociology of journalism as a starting point, Mcnair explores why the concept of objectivity can and must be reassessed in the digital age [7]. Ferrucci’s research aims to examine whether this relatively new market model practices a new form of public journalism. It is also a previous study called Public Service Journalism [8]. Mitchell and Lim characterize the r/SyrianCivilWar community. These are algorithm-driven public discourse, deliberate communication, reflexivity and transparency, and database journalism [9]. Lei et al. combine network analysis and Granger causality test to explain media effects. He employs network visualization techniques to graphically represent the media network agenda [10]. Wahl-Jorgensen et al. in the context of a quantitative content analysis of 2007 and 2012 procurement patterns for BBC radio, television, and online news programmes. He reconsidered the concepts of balance and impartiality in journalism [11]. Seethaler and Beaufort’s analysis shows that what people pay attention to is no longer broadcast news itself, but the coexistence of several images of the role of broadcast news and its functional concepts [12]. Eric and Chen proposed a neural network model of hippocampal-cortical interaction. He explored the impact of dysfunction on hippocampal-cortical interactions through simulation experiments [13]. Hecquet and Brochet also compare some typical results with the measured values. Its accuracy is sufficient to evaluate the permeance network model [14]. Payal et al. detailed a stochastic model for EPN, inspired by a branch of queuing theory called G-networks [15]. These methods provide some references for the research. However, due to the short time and small sample size of the relevant research, the study has not been recognized by the public.
This paper provides an in-depth analysis of model selection for deep belief networks in deep learning. Since the deep belief network is formed by stacking RBMs, the model selection of the deep belief network is essentially the model selection of the RBM. It mainly analyzes the probability distribution of variables in the visible and hidden layers of binary RBM, Gaussian RBM, mean-covariance RBM, and categorical RBM from a statistical point of view. At the same time, it analyzes the probability distribution of each layer of the deep belief network and the algorithms used in the training model, namely, contrastive divergence and continuous contrastive divergence. It analyzes how three types of RBMs use annealing importance sampling to estimate the partition function and then further estimate the log-likelihood of the model to the data. The choice of the model mainly lies in the choice of the base model and the derivation of the calculation formula. In Gaussian RBM, considering that the visible layer is a continuous distribution, the base model is adjusted accordingly. In the mean-covariance RBM, since the samples of the base model and the samples of the intermediate distribution are difficult to obtain, the samples are obtained by sampling the HMC, and the partition function is estimated by combining with annealing importance sampling, thereby estimating the log-likelihood of the model to the data. In conclusion, the model selection method of deep belief network proposed in this paper is more credible than the method of reconstruction error. It has certain application value in practice. However, in the process of selecting the RBM model, the estimation of the partition function of the trained binary RBM and Gaussian RBM generally takes less time if the amount of data is not large, otherwise, it takes a long time. However, the estimation of the partition function for the mean-covariance RBM takes a long time. Therefore, the computer requires a high configuration, and researchers must be patient enough. Due to the limited ability, in the process of empirical analysis, for the selection of hidden units, the article samples the whole hundred, and there may be a better number of hidden layer units that can be selected. Based on the current information distribution method, the mobile communication client can accurately communicate to users through background intelligent data. It saves the time cost of users looking for information, improves user experience, enhances stickiness, and stimulates potential users. Precise communication will also have a positive impact on the social production mode on the basis of enhancing the media value and communication efficiency. All in all, the recipients largely determine the operation of news media organizations. The main body of news dissemination has also undergone corresponding changes [16].
2. Restricted Boltzmann Machines and Deep Belief Networks
Since the deep learning model was proposed, it has been applied in many fields due to its good results in major competitions. As an important submodel of deep learning model, RBM model has been successfully applied in many fields, such as dimensionality reduction, information retrieval, time series modeling, and speech recognition. Research on RBM and deep learning models has always been a hot spot in this field. First of all, it briefly introduces the predecessor of RBM-Boltzmann Machine (BM for short). Second, it starts from a statistical point of view. It analyzes the RBM variant models binary RBM, Gaussian RBM, mean-covariance RBM, and categorical RBM, analyzes the probability distribution of each variable set and a single variable, and then gives the statistical interpretation of the deep belief network model. Finally, it introduces two training algorithms for RBM model and DBN model—CD and PCD.
The purpose of Boltzmann machine learning is that the probability distribution of the model is equal to the probability distribution of the training data. If the maximum likelihood method is used to train the parameters, because the model is complex and contains too many variables, the gradient value is difficult to calculate, so the sampling method is generally used to approximate. These methods mainly include Gibbs sampling, random approximation, parallel annealing, etc. However, it can be seen from Figure 1 that the BM model has a complex structure. There are connections between visible layer variables and hidden layer variables, between visible layer variables and visible layer variables, and between hidden layer variables and hidden layer variables. This makes model training very difficult, takes a lot of time, and may not get accurate probability distribution. In order to simplify the training of this model, it only connects visible layer variables and hidden layer variables. There is no connection between other variables, which makes it easy to solve the probability distribution of the model. It was later called a Restricted Boltzmann Machine (RBM for short).
2.1. Basic Characteristics, Performance, and Realistic Basis of Media Intelligence
Traditional intelligence is generally the embodiment of media intelligence. Media theorists believe that “the medium is the message,” that is, understanding the medium as meaningful information. At this stage, with the gradual progress and maturity of artificial intelligence technology, human society has gradually entered the era of intelligent media. Media intelligence also has a huge impact on the journalism industry, promoting changes and reforms in the journalism industry, and has a huge impact on the way news is disseminated.
In the process of media development, news communicators must not only respond to economic interests but also respond to communication efficiency. The development of the media in pursuit of economic interests is understandable. But it is obviously unscientific to only focus on economic interests without considering the geographical and resource conditions of various media dissemination. Therefore, the development of media should pay more attention to the efficiency factor, rather than abandoning the foundation. The operation and growth of an organization should not only focus on adopting specific methods to achieve the goals of the organization but also solve the problem of operational efficiency, improve efficiency, and finally obtain the highest output with the least input. Effectiveness largely reflects an organization’s ability to work and skill levels. Efficiency assessments are slowly becoming an important criterion for measurement and evaluation and are used in all contexts. Searching with the keyword “efficiency evaluation” on CNKI, there are as many as 5,960 journal articles for research. It has carried out “efficiency evaluation” in agriculture, education, and other industries. But journalism dabbles in another dimension and angle. By analyzing and sorting out relevant research literature, the media industry uses “benefit” to evaluate media rather than “efficiency.” The level of economic and social benefits is the manifestation of the social status of news media. Higher economic strength enables news media to gain competitive advantage and healthy development. For some news media pursuing long-term development, it is understandable that benefit becomes an important indicator of their evaluation. The development effectiveness of news media focusing on efficiency has its own evaluation method, as shown in Figure 2.
Prior to this, the “China Journalism Annual Development Report” was released. The report shows that China’s journalism has ushered in a new life in the transformation. Relevant reports show that in 2017, the news media industry is more proficient in the use of new media technologies such as video and animation and pays more attention to the visual presentation of content. Short video is the keyword of the year in 2017. The report also predicts that the short-term news position in 2018 cannot be underestimated. Moreover, super short videos, some live video broadcasts, virtual videos, and real videos will all show a growth trend. According to the 40th “Statistical Report on China’s Internet Development,” as of June 2017, the number of mobile Internet users has increased steadily, reaching 724 million, and the proportion of mobile Internet users is as high as 96.3%, as shown in Figure 3.
The above characteristics of WSN make it significantly different from existing networks in terms of network organization and survival time, as shown in Table 1.
It divides the trust into the trust level according to the value interval, and the specific division form is shown in Table 2.
Media such as print media, radio, and television have slowly developed into traditional media at a very early stage. Although these traditional media have strong administrative control and financial support, their operating conditions have not improved significantly. And users spend less time on these media. Market economic factors can affect the development of communication media (overcapacity, large inventory, and other problems in the development of traditional media). It has little to do with the traditional media’s unwillingness to change, but is caused by reasons such as the pursuit of a “high-level” media structure. From the optimistic point of view, the development of traditional media has a lot to do with its own production capacity and excess inventory. Therefore, it is necessary to actively promote the healthy and orderly development of traditional media. Figure 4 shows the scale of Chinese netizens and the Internet penetration rate from 2015 to 2019.
The weight in direct trust (that is, the adaptive penalty factor) is only related to the state of the current transaction. Therefore, the influence of the evaluation of failed transactions should be increased, and the influence of evaluation of successful transactions should be reduced. If a node successfully provides services several times in a row after a failed transaction, it means that the failed transaction of the node is not malicious behavior or the node has changed from a malicious node to a good one. Therefore, after each successful transaction of the node, the influence of the successful transaction of the node is further increased. However, if the node provides bad service again, then, the node is likely to be an oscillating node, and the punishment for the node must be increased. Therefore, the impact of current failed transactions should be increased, and the impact of future successful transactions should be reduced. Based on the above analysis, the paper introduces the idea of congestion control in computer networks. In the initial stage of the P2P network, the requesting node relies too much on the trust value calculated by the general trust model when selecting the service node. At the same time, the recommendation trust degree in its trust value is not accurate enough, resulting in a low transaction success rate. This paper studies the use of random factors to jump out of the local optimum in intelligent algorithms and introduces the reliability factor of trust value in the initial stage of the trust model. Therefore, the requesting node does not select the node with the largest trust value, but randomly selects the service node, as shown in Figure 5.
A distance-based wireless sensor network trust model identifies a distance dimension, centered on a specific location. It divides cluster trust levels according to distance, including energy trust based on transfer distance, ethical trust, and recommendation trust distance based on interaction and capability trust. The cluster head election algorithm is executed when the model starts to operate or when the specified time interval is reached. It selects or updates the cluster head node and broadcasts the cluster head information to all nodes in the cluster. Figure 6 shows the trust model of wireless sensor network based on the physical distance and interaction distance of nodes.
2.2. Gaussian Restricted Boltzmann Machine
Although the binary RBM is a good feature detector, since the visible layer variables are binary. In actual analysis, the variable information must be binarized first, so that useful analysis information will be lost more or less. In the Gaussian RBM model, the variables of the visible layer obey the Gaussian distribution, and the variables of the hidden layer are the same as the binary RBM and obey the binary distribution. The energy function and joint probability distribution of a Gaussian RBM are
It cares more about the marginal distribution of visible variables.
Since the visible layer variable obeys the Gaussian distribution, the following analysis is made:
The formula has the following decomposition:
The probability that the strain vector takes a value of 1 is
The probability distribution of an undirected graph is defined as
The contribution value is
On the contrary, it means that the node trusts the interactive experience of the recommended node more.
3. Analysis and Results
Articles will use the Kiousis media exposure metric. Media popularity is divided into three levels: popularity, coverage, and dimension. Popularity refers to the importance of news topics in the context of media news. The study was the first to document the order. Coverage level is the news media’s information about a news topic, reflected in the number of news and the layout size of the news plan for that topic. The more news occurrences of a certain topic, the higher the significance of the topic. The news layout is for newspapers, and the news layout is closely related to the word count of the news. Therefore, in the WeChat public account, we measure the media salience by measuring the number of news words. The dimensional level refers to the emotions displayed by the news media on news issues. The research will use Kiousis to divide emotions into two categories: feeling and nonfeeling. When analyzing the text, the report tone was divided into positive, negative, and neutral. Positive and negative are both sentimental evaluations, and neutral is nonsentimental evaluations. The so-called positive tone means that the overall news tone is mostly optimistic or praiseworthy, such as that it is helpful to life. Negative tone means that the overall news tone is mostly negative or critical, such as that it will cause adverse effects. Neutral means that there are no positive or negative comments in the news. The media salience of self-media is studied by measuring three variables of prominence, attention, and dimension. In the research of audience feedback on self-media science news dissemination, the author will study the number of readings and the number of likes of each article as dependent variables. The more the number of readings and the number of likes of the article, the more the article is liked by the readers, and the better the audience feedback is obtained.
Timeline is the most common form of visual news, and it originated from news reports in the United States. This kind of timeline news report, specifically, uses Internet technology to connect events in chronological order. It forms a recording system and presents it to users in the form of pictures and texts. The biggest effect of this presentation method is that it can present the events that have occurred systematically, completely, and precisely. News has six elements, namely, “5 W +1H,” which should be kept in mind by every journalist. The key to the product composition of the timeline is not the six elements, but the neglected element “time.”
A news event is a recent fact, but also a fact that is dynamic over time. Therefore, the timeline is more able to complete the event in a way of “connecting the context,” and it pays more attention to the publication of “thematic creativity,” and constantly adapts to promote innovation. In addition, a minority of respondents cited “image appeal” and “cover design” as the main factors in persuading readers to buy traditional publications and fulfilling them, as shown in Figure 7, Table 3.
In the research question stage, in the second research question, what are the factors that affect the prominence of social media? Are the scientific topics, scientific issues, news sources, and article images mentioned in the article the main factors that affect the salience of We-Media? The above four factors and the three levels of media saliency of prominence, attention, and dimension were analyzed by using SPSS data analysis software. The results obtained are shown in Tables 4 and 5.
The first form of micromedia that people are familiar with is blog, which once led the Internet trend at that time. Blog, refers to the network log, is a simple and fast publishing platform for personal information and original content. Once it appeared, it has won a wide range of users with its characteristics such as personalization, openness, serial log form, interactivity, multimedia, hyperlinks, and relatively simple operation. It can be seen from the survey data that more and more people choose to read through the use of new media in the choice of reading methods. In allocating reading time, the time spent reading through traditional media is greatly reduced. The reading styles, reading habits, reading motivations, and reading tastes of the reading public have changed at different levels. This survey also shows the reasons for these shifts. For example, in a survey on the pros and cons of reading new media, 34% of respondents believed that the benefit of reading new media was “huge information,” 21% of the respondents believe that its advantages are “fast,” and about 20% of the respondents believe that its advantages are “convenience” and “interactivity” (Figure 8).
Although with the gradual increase in the share of new media reading, traditional paper reading has been hit to a certain extent. As a long and important form of media in the history of human communication, it must have irreversible benefits. In the subject survey with related questions, it was found that the greatest benefit of reading traditional papers was “depth of content.” Some people also think that the role of reading content is comprehensive, the collection value is high, and it is in line with reading habits. Less than 10% of the subjects chose “less typos” and “the typesetting is worth reading.” It is undeniable that the innovation of new media technology has led to changes in reading carriers, further compressing the traditional paper-based reading space.
In addition to the benefits of reading in new media, awareness of this change in the existing traditional paper-based reading style also becomes a key factor. In a traditional paper-based dyslexia survey, nearly half of respondents cited “unchangedness” as a major flaw in traditional paper-based reading. About 20% of the respondents believe that too much trouble and compact reading space are the biggest drawbacks of traditional paper reading, and other defect options are “fragile,” “takes up space,” and “environmentally friendly” (as shown in Figures 9 and 10.
4. Discussion
With the development of the times and the advancement of science and technology, the slightest change is also affecting the development direction of the dissemination of current affairs reports. In the context of new media, we can no longer simply use current affairs reports as a tool for propaganda, but should treat it as a product to operate. With the emergence of new media, everyone has a microphone, and the “civilian,” “story-based,” and “diversified” reports are inevitable. This requires us to have more guidance, more dissemination, more influence, and more credibility on the way to disseminate policies. The most core part is to insist that content is king and to lead the content in the correct political direction. News reports, especially reports of political content, blindly expand the boundaries of content production, and incremental content will outweigh the gains, so it is necessary to keep the content well. In the face of the impact of new media, the “depth” and “reliability” of content cannot be lost. This is in line with the nature of the Ministry of Communications and the law of news. Compared with the massive information gathering ability of new media, traditional media has inherent disadvantages. Moreover, the current affairs news report itself is not as rich in content as other people’s livelihood news. Its advantage is not in the dryness of the content, but in the authority and the foresight of future life. A country, a society, and all kinds of life are inseparable from politics. Politics is a guide to the future and a direction for a country’s development path. On the contrary, we must know that the “depth” and “reliability” of content are both the disadvantage of new media and the height that new media has always hoped to snatch. Whether it is “political explanation” or “today’s topic,” they all hope to do the same in-depth and authoritative news reports on current affairs. However, because they have neither authoritative sources nor authoritative voices, they can only be reposters in many cases.
During the anticorruption storm in 2016, Internet celebrities could only passively reprint surging news, which explains everything. Therefore, in the context of new media, current affairs news reports should remain authoritative, truthful, and serious, political content should be political, and science, education, and health content should be policy-oriented. It is necessary to be firm in the correct political direction, not to lose the high ground of content, and not to lose the advantages in their own hands. No matter how public discourse develops in the new media context, the authority of current affairs news must be reflected in the content. Only in this way will there be credibility, current affairs news will have room to speak out, and it will not affect the authority of the reported content. It may be able to enhance its intimacy with the public in content such as headlines, pictures, and videos, but it must not play tricks on the content of the report. The trend of current affairs reporting, and the most important point, is the change of technology intermediary. Technology brings about changes in platforms as well as changes in the pattern of innovation and dissemination. Proficiency in technology and the use of new media dividends are important means of current affairs news innovation. The reason why new media can provide massive information resources lies in the advantages of technology. As traditional media explore the way of integrating media, current political news can also be brilliant on the mobile terminal. Some serious and boring content, through the packaging of technical means, can attract the public’s attention resources in a short period of time. It makes mainstream thinking more deeply rooted in the hearts of the people, and the interpretation of policies makes more people understand.
In recent years, the image of leaders in current affairs news reports has also begun to change from authoritative and rigid to life-like, using a kind of emotional politics to drive rational politics. The so-called perceptual politics refers to the use of irrational things in maintaining political power that can mobilize people’s emotions. This political approach is more warm and intimate. On the one hand, the current affairs news reports with the friendly image of the leaders will prevent the public from having dyslexia when reading. On the other hand, it can also make the public more willing to understand political content and more willing to participate in political life.
5. Conclusion
With the development of technology and the traditional newspaper industry’s emphasis on technological dividends, in the future, current affairs news reports will open up a larger market. In the context of new media, there will be more room for changes in current affairs news reports in the future. Although we still have to insist that content is king, we cannot give up technology, let alone ignore the times. As the mouthpiece of the party and the people, we must understand the importance and arduousness of the task of innovation in current affairs news reports. To be firm in the new era, innovation in news coverage of current affairs lies at the core of voice. It is necessary to make full use of the advantages of all technologies at home and abroad to create a stage suitable for current affairs news reports. We need to use the voices to defend the mainstream public opinion positions and lead the country in the correct political direction. The article’s innovative research on current affairs news dissemination has achieved results to a certain extent. But the research involving party newspapers and current affairs reports is very broad. With the development of technology and the growth of new media, current affairs news will also undergo further changes. Therefore, there is still much room for further research. At present, Chinese and foreign industries have already carried out practice in many aspects. Judging from the findings, media intelligence has a series of characteristics such as “everything is a medium, self-evolution and human-machine symbiosis.” On this basis, algorithm news, Internet of Things news, robot news, and other methods have been born. In the future, it will redefine the characteristics of news gathering and production, broaden the channels of news gathering, and make the main body of news dissemination have a far-reaching influence. Through various analyses of this research, it is found that this paper believes that in the future, media intelligence will have a greater impact on news collection, production, distribution, and review, and this impact will be lasting. The traditional professional media people will also actively transform with the changes in the media environment. At the same time, the fake news caused by the mimetic environment, the blind worship of too irrational technology, and the over-reliance on new media will finally make people reunderstand the combination of tradition and technology. In terms of theoretical support, many experts and scholars are still needed to provide improved countermeasures and suggestions for the innovation of current affairs news communication, and more examples are needed to prove the operability of the research.
Data Availability
The data used to support the findings of this study are available from the corresponding author upon request.
Conflicts of Interest
The authors declare no conflicts of interest.