Exploration of the digital dissemination mechanism of red culture in youth ideological and political education
Data publikacji: 17 mar 2025
Otrzymano: 14 paź 2024
Przyjęty: 29 sty 2025
DOI: https://doi.org/10.2478/amns-2025-0284
Słowa kluczowe
© 2025 Yaxu Lei et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
At present, the wave of red culture learning is flourishing, and the demand for the protection and inheritance of red resources, red genes and red spirit is more and more urgent, from the historical heritage to the situation and policy, the excavation, development, utilization, integration of red cultural resources, research and practice have ushered in the best opportunity for development [1-3]. Red culture, as a flower born on the Chinese soil, is a powerful driving force for the construction of a strong socialist culture, and is a valuable wealth and cultural source that people cannot discard [4-6]. As the excellent promoter and inheritor of Chinese culture, the Communist Party of China (CPC), since the day of its establishment, has shown that the red culture is a guiding light to guide the development of China. The red culture has not only united people’s determination to fight for the future, inspired and united people around the Party, but also promoted people’s awakening to the nation and themselves to a great extent, so that the CPC and the Chinese people can achieve victory in the cause of revolution and democracy [7-9]. In a word, the red culture has been formed and developed throughout the various stages of Chinese history. During the new democratic revolution and the subsequent socialist construction, the red culture has exerted its powerful cultural cohesion and produced a great impetus. Therefore, in order to realize the great rejuvenation of the Chinese nation and the “Chinese dream” for the benefit of all Chinese people, it is more necessary for people to inherit and carry forward the red culture inherited from the old generation of proletarian revolutionaries [10-12].
Red culture is an important resource for ideological and political education in colleges and universities, and it is also an important spiritual wealth left behind by the revolutionary forefathers. To cultivate, inherit and innovate red culture is an important way to cultivate and carry forward socialist core values and improve the effect of ideological and political education of college students [13-16]. In the face of the current deficiencies in the dissemination of red culture in colleges and universities, colleges and universities should vigorously carry out the digitization of ideological and political education, and actively respond to the strategic policy of informationization and strengthening the country. Combined with digital technology, the traditional red culture is integrated into the education and teaching in colleges and universities, inherits the red gene, promotes the construction of ideological and political informatization in colleges and universities and the reform of teaching, which helps to cultivate new era college students with ideals, competence, and commitment, and realizes the fundamental task of establishing moral education in colleges and universities [17-20].
After studying red culture and its digital communication methods, the article constructs a model of influencing factors for the digital communication of red culture in youth ideological and political education. According to the constructed model of influencing factors, the influencing variables are refined and relevant hypotheses are proposed. To empirically analyze the influencing factors of digital communication of red culture, basic demographic information of the respondents and the audience’s perception of digital communication of red culture are obtained through questionnaires. Subsequently, the correlation between each influencing factor and the communication effect is analyzed. The proposed hypotheses were evaluated using structural equations, and the effects of the influencing factors on their interaction were further analyzed. Based on the findings, the operational mechanism of digital communication of red culture in youth ideological education is summarized.
Red culture was formed in the period of Chinese revolution, construction and reform, and in the process a set of ideology, spirit and value system with distinctive features was formed [21]. In a narrow sense, red culture is the sum of material and spiritual wealth created in the process of China’s construction, and the connotation of red culture is elaborated in terms of material red culture and non-material red culture.
Red culture is a specific red theme and spirit formed by the Chinese people through long-term revolutionary practice and continuous integration of Chinese excellent culture.Red culture consists of both material and non-material red cultures. In this process, physical objects, sites and cultural relics, etc. Related to the Red Revolutionary War, these items have unique historical, cultural, and value connotations. These objects, sites, and cultural relics, etc. are called material red culture, and these material relics represent the will, philosophy and struggle of the Chinese people, and have strong political and historical significance, and the inheritance of the material red culture can maintain our memory of the revolutionary history. At the same time, during the process, the deeds, political beliefs, spirituality, and institutional culture were recorded, and then created into poems, songs, movies, plays, and so on. These written records and literary works are called intangible red culture. The creation and dissemination of intangible red culture is not just a way to express revolutionary feelings and ideal beliefs. Moreover, it can deepen people’s understanding of revolutionary history and spirit through art, unite people’s hearts, and strengthen their power of unity and struggle. Excellent literary and artistic works of revolutionary revolution can carry forward the glorious traditions and fine qualities of revolutionary martyrs, and cultivate followers and supporters of the national cause. Of course, the connotation of red culture will continue to be enriched, incorporating new cultural connotations and carrying the spiritual connotations of each period, which is an important spiritual impetus for us to realize the great renaissance, and also an important material for cultural education in colleges and universities.
The rapid development of information technology is reshaping the way people socialize, work, and play. Digital culture is widely circulated and diversely displayed. In particular, red culture, as a cultural heritage carrying rich history and deep connotations, faces unprecedented challenges and opportunities for its dissemination in the digital era. Information technology provides a unique platform that not only breaks through the limitations of physical space to create an immersive experience, but also enhances user participation through interactivity, thus making the dissemination of red culture more vivid and effective.
Technological innovation has always been the key driving force for the evolution of cultural communication. Under the background of informationalization, the digital communication of red culture faces unprecedented opportunities and challenges. The integration of advanced technologies such as Virtual Reality (VR), Augmented Reality (AR), and Artificial Intelligence (AI) provides a brand new platform and communication path for this specific cultural content. The traditional linear and one-way communication mode is no longer adapted to the users’ demand for interactive experience and participation, and the Internet allows users to interact with red culture in real time through immersive experience, thus forming a new mode of communication that is multi-dimensional, interactive and highly participatory. For example, the three-dimensional reenactment of historical events not only attracts users’ visual attention, but also inspires them to think about and explore the deeper meaning of red culture. In addition, blockchain technology ensures the transparency and traceability of the cultural communication process, providing technical support for the authenticity and authority of red culture.
Cross-media narrative refers to the construction of a coherent story world in multiple media forms [22]. In the information-driven environment, this narrative provides a strong impetus for the digital dissemination of red culture. Red culture stories can cross the boundaries of virtual and real worlds, games and learning, entertainment and education, and appear in front of users in rich and diverse forms. Under the framework of cross-media narrative, red culture is no longer limited to fixed expressions and channels, but can be vividly presented in a variety of forms, such as digital art, interactive games, and online education. This approach not only deepens users’ understanding of the connotation of red culture, but also increases the contacts and depth of cultural dissemination, effectively embedding the story clues and educational significance of red culture into the digital content that users come into contact with on a daily basis, thus realizing the seamless transmission and deep penetration of cultural values.
In this chapter, through the analysis of existing theories and literature, the influencing factors of the digital dissemination of red culture in youth civic education are proposed in accordance with the framework of the 5W communication model, and then the influencing factor model is established, and the relevant hypotheses are established according to the model [23]. Starting from the relevant assumptions to build the questionnaire of each dimension of the influence factor model, carry out a large-scale questionnaire survey and collect data, use SPSS 20 to carry out descriptive analysis and factor analysis of the data, verify the assumptions by analyzing the results, and amend the model diagram of the influence factors according to the verification results, and finally come up with the specific factors affecting the digital dissemination of red culture.
According to the existing theories and literature analysis, it can be seen that scholars have a wide range of research on influencing factors, but they can be roughly divided into the aspects of the elements of the 5W communication model, media technology, social and cultural environment, government policies and other aspects. By organizing and analyzing the literature and combining the research content of the 5W communication model, the author divides the research indicators of influence factors into three levels, which are:
1) Individual level: audience’s personal attributes, degree of interest in red culture. 2) Social level: government policy, cultural environment and media environment. 3) Communication process level: media technology, communication content and communication talents.
The individual level and the communication process level influence the social level to a certain extent. Table 1 shows the corrections made by the author based on the study’s specific situation.
Influencing factor index system
| Source level | Influencing factor |
|---|---|
| Personal level | Individual attribute (IA) |
| Interest (I) | |
| Social level | Government policy (GP) |
| Cultural environment (CE) | |
| Media environment (ME) | |
| Promotion process level | Media technology (MT) |
| Promotion content (PC) | |
| Promotion talent (PT) |
According to the constructed model of influencing factors, eight variables were extracted, and then the hypotheses of influence on the digital dissemination of red culture were established as follows.
Social typology theory holds that “audiences can be categorized, and although the personality of each recipient varies greatly, different social types will be formed in a certain social class due to the fact that the audiences are the same or similar in terms of gender, age, region, ethnicity, occupation, salary income, religious beliefs, and literacy level. Audiences of a particular social type will in turn respond to the same message in a broadly consistent manner.” Audiences with different personal attributes are an important research object in the communication process, so this study uses the audience’s personal attributes as a research variable and formulates hypothesis H1.
H1: Audience’s personal attributes have a significant effect on digital communication of red culture.
Identifying the level of audience interest in red culture is a crucial task in distributing information. When the audience is interested in red culture, there is a high demand for information about it, and the more information received about it, the greater the desire for it. Does identifying audiences who are interested in red culture information and targeting information dissemination to them have an effect on the dissemination of red culture?This study takes the audience’s information demand as a research variable and makes a research hypothesis H2.
H2: The degree of interest of the audience has a significant effect on the communication effect of red culture.
Government policy is the “windmill” of all aspects of social construction, and the impact of policy is more deeply rooted in all aspects of daily life. The government policies on red culture, such as compulsory education on red culture, financial subsidies for red culture dissemination, increased investment in red culture, etc., do they have a certain impact on the dissemination of red culture? Therefore, based on the above analysis, research hypothesis H3 is proposed.
H3: Government policies have a significant effect on the digital dissemination of red culture.
With the gradual acceleration of the process of political and economic globalization, cultural exchanges among countries are more and more, and the homogeneity of culture has increased, and cultural integration has become a trend that must be unstoppable. Will such a cultural environment have a certain impact on the dissemination of red culture? Therefore, this study supports the hypothesis H4.
H4: The cultural environment has a significant effect on the digital communication of red culture.
The current red culture follows the mass media into the digital era together, which brings challenges and changes to all aspects of red culture. Many of the connotations of red culture can only be experienced, not transmitted. Does the current digital media environment have a certain impact on the dissemination of red culture?This study supports the hypothesis H5.
H5: The media environment has a significant effect on the digitalized communication of red culture.
The development of media technology has given rise to the emergence of new media as well as cell phone APP, and the red culture has appeared a new medium for the dissemination of information, and this new medium has changed the established communication habits of the red culture communication, which has brought new opportunities and challenges for the dissemination of red culture. The new mass media can maximize the dissemination of the information of red culture, and the modern communication development of red culture needs to rely on the media technology of mass media, and the media technology can make the communication of red culture keep up with the trend of the times. Does media technology have some influence on the communication of red culture? This study makes hypothesis H6.
H6: Media technology has a significant effect on the digital dissemination of red culture.
The communication content of red culture plays a direct role in the reaction mechanism of the audience and has an important position in the communication process, and different communication content will have different effects on the audience. Does communication content have a certain influence on the spread of red culture? This study makes the following hypothesis H7. H7: The communication content of red culture has a significant effect on the digital communication of red culture.
Under the current digital media environment, red culture communication talents need to have all-round and multi-disciplinary knowledge, so that excellent communication talents become more and more scarce, and the content quality of red culture will not be guaranteed. Does communication talent have some influence on the communication of red culture? This study makes the following hypothesis H8.
H8: Red culture communication talents have a significant effect on the digital communication of red culture.
In this paper, the age of youth was determined as 18-35 years old by reference to multiple definitions. Preliminary statistics were conducted using a questionnaire survey. A total of 700 questionnaires were distributed, 652 questionnaires were collected, and the questionnaires were screened by the option of “Have you been exposed to red digitized content?” After excluding invalid questionnaires, there were 445 valid questionnaires. Specific demographic data are shown in Table 2.
Descriptive statistical results
| Variable | Classification | Number | Proportion |
|---|---|---|---|
| Gender | Male | 218 | 48.99% |
| Female | 227 | 51.01% | |
| Age | 18-24 | 268 | 60.23% |
| 25-29 | 109 | 24.49% | |
| 30-35 | 68 | 15.28% | |
| Education background | Senior school/secondary specialized school/technical school and below | 30 | 6.74% |
| Junior college | 42 | 9.44% | |
| Undergraduate | 239 | 53.71% | |
| Postgraduate and above | 134 | 30.11% | |
| Average monthly income ( |
≤1000 | 152 | 34.16% |
| 1000-3000 | 126 | 28.31% | |
| 3001-5000 | 71 | 15.96% | |
| 5001-7000 | 45 | 10.11% | |
| 7001-10000 | 34 | 7.64% | |
| >10000 | 17 | 3.82% |
The characteristics of the sample are as follows: in terms of gender, there are 218 males, accounting for 48.99%, and 227 females, accounting for 51.01%, which is a relatively balanced ratio between males and females in the research sample. In terms of the age of the respondents, 18 to 24 years old accounted for 60.23%, 25 to 29 years old accounted for 24.49%, and 30 to 35 years old accounted for 15.28%, which shows that the people who contact or use red culture digitization on a daily basis are mainly under 30 years old, which is also consistent with the fact that the digital technology is more likely to be widely disseminated among young people. In terms of the education level of the respondents, the proportion of people with bachelor’s degree is the largest, accounting for 53.71%, master’s degree and above accounts for 30.11%, college degree accounts for 9.44%, and high school/secondary school/technical school and below accounts for 6.74%, which shows that, combining with the age distribution of the respondents, the group of people who have been exposed to the digitization of the red culture is dominated by the group of those who have received higher education level. The group is dominated by the group with higher education level. In terms of average monthly income, those with less than 1,000 yuan, 1,000 to 3,000 yuan, 3,001 to 5,000 yuan, 5,001 to 7,000 yuan, 7,001 to 10,000 yuan, and more than 10,000 yuan accounted for 34.16%, 28.31%, 15.96%, 10.11%, 7.64%, and 3.82% respectively.
In the second part of the questionnaire, the basic situation of the audience’s contact with the digital communication of red culture is designed to grasp the current contact situation of the respondents with the digitalization of red culture and the current situation of communication, to present the realistic background of this study, and at the same time, according to the respondents’ contact with and use of the digitalization of different red cultures, it is convenient to put forward relevant strategies and recommendations in relation to the actual situation of the digitization of red culture. Strategies and Suggestions.
The top ten red culture digitization channels and methods are shown in Table 3. In conducting the basic survey on the audience’s contact and use of red culture digitization, it was found that among the 445 respondents, 340 people came into contact with red culture through the digitization of red culture short videos, accounting for 76.40%, followed by digital museums micro-letter applets or APPs, accounting for 73.03%, and then documentaries related to red culture, accounting for 63.15%.
Red culture digital tools and ways of audience
| Ranking | Red culture digital promotion way | Number | Proportion |
|---|---|---|---|
| 1 | Red culture short video | 340 | 76.40% |
| 2 | Digital museum (APP/small program) | 325 | 73.03% |
| 3 | Red culture documentary | 281 | 63.15% |
| 4 | Scan electronic books about red culture | 228 | 51.24% |
| 5 | Red culture immersive virtual interaction system with AR and VR | 225 | 50.56% |
| 6 | Red culture database website | 198 | 44.49% |
| 7 | Red culture broadcast and TV program | 187 | 42.02% |
| 8 | Red culture content on social media | 184 | 41.35% |
| 9 | Red culture music | 182 | 40.90% |
| 10 | Digital product with red culture factors | 180 | 40.45% |
The order of the most impressive digital content of red culture is shown in Table 4. The survey found that the digitized content of red culture categories such as red culture art and red culture music, which are more familiar to the public, left the deepest impression on the audience, and more than half of the respondents said that they were deeply impressed by the red culture of the art category and the music category. On the other hand, music and art are relatively unfamiliar to young audiences, especially the music and art category of red culture, and only 9.44% of the respondents had a deep impression of the digital content of the music and art category of red culture.
The ranking of the most impressive red culture content
| Ranking | Red culture digital content | Number | Proportion |
|---|---|---|---|
| 1 | Red culture painting | 244 | 54.83% |
| 2 | Red culture music | 228 | 51.24% |
| 3 | Red culture literature | 168 | 37.75% |
| 4 | Red culture drama | 140 | 31.46% |
| 5 | Red culture dance | 106 | 23.82% |
| 6 | Red culture Quyi | 42 | 9.44% |
Correlation analysis is a data analysis method that examines the closeness of correlation between variables. According to the research hypothesis, this study needs to measure the correlation between the influencing factors such as audience’s personal attributes (IA), the degree of interest in red culture (I), government policy (GP), cultural environment (CE), media environment (ME), media technology (MT), communication content (PC), and communication talents (PT), and the communication effect (PE), and when the above relationship is established, the study can continue with the next step of the study.
In this study, Pearson’s correlation coefficient method was used to analyze the correlation between the influencing factors, and the results of the correlation analysis are shown in Figure 1. As can be seen in Figure 1, there is a significant correlation between the audience’s personal attributes, interest in red culture, government policies, cultural environment, media environment, media technology, communication content, communication talents and communication effects, with the correlation coefficients of 0.487, 0.478, 0.563, 0.587, 0.588, 0.583, 0.689, 0.711, respectively, and P values were less than 0.01, thus significant correlation.
Correlation analysis of influencing factors
Using the structural equation modeling method, based on the structural equation research model of the effect of digital communication of red culture in Chapter 3, AMOS23.0 software was used for statistical analysis to obtain the estimation results of the model correlation path coefficients as shown in Table 5. From Table 5, it can be seen that the standardized path coefficients of hypotheses H1, H2, H3, H4, H5, H6, H7 and H8 are 0.162, 0.149, 2.012, 1.090, 0.332, 0.175, 0.932, 0.253, respectively, with the P-values of less than 0.05, which indicates that hypotheses H1~H8 are valid.
Path relation test results
| Research hypothesis | Path relation | Nonnormalized coefficient | SE | Z | P | Estimate | Result |
|---|---|---|---|---|---|---|---|
| H1 | IA→PE | 0.146 | 0.107 | 5.047 | 0.003 | 0.162 | YES |
| H2 | I→PE | 0.158 | 0.138 | 3.704 | 0.002 | 0.149 | YES |
| H3 | GP→PE | 0.231 | 0.135 | 5.32 | 0.000 | 2.012 | YES |
| H4 | CE→PE | 0.222 | 0.116 | 5.547 | 0.000 | 1.090 | YES |
| H5 | ME→PE | 0.133 | 0.065 | 4.94 | 0.000 | 0.332 | YES |
| H6 | MC→PE | 0.220 | 0.096 | 3.286 | 0.001 | 0.175 | YES |
| H7 | PC→PE | 0.237 | 0.116 | 2.858 | 0.003 | 0.932 | YES |
| H8 | PT→PE | 0.175 | 0.318 | 4.129 | 0.000 | 0.253 | YES |
Based on the above hypotheses, this paper further proposes the mediating effect hypothesis as follows:
H1a: Audience personal attributes affect the red culture digital communication effect by influencing the audience’s red culture interest degree. H3a: Government policies affect the digital communication effect of red culture by influencing the cultural environment. H3b: Government policies affect the digital communication effect of red culture by influencing the media environment. H3c: Government policy affects the digital communication effect of red culture by influencing the communication content. H4a: The cultural environment influences the digital communication effect of red culture by influencing the communication content. H4b: The cultural environment affects the digital communication effect of red culture by influencing communication talents. H5a: The media environment affects the digitalization of red culture by influencing media technology. H5b: The media environment affects the digital communication effect of red culture by influencing the communication content. H5c: The media environment affects the digital communication effect of red culture by influencing communication talents.
This paper uses AMOS23.0 software to test the significance of the mediating effect between the influencing factors of the digital communication effect of worry culture and the communication effect using the confidence interval method. Set the confidence interval method to 1000 times for extracting the sample, with a confidence interval set at 95%. According to MACKINNON et al. Experimentally, it was concluded that the method of bias correction in the nonparametric bootstrap method is optimal, therefore this study reports the correction of bias and percentile confidence intervals. If there is no zero in the confidence interval (CI), the mediation effect is significant. Table 6 displays the results of the mediation effect test.
The test results of mediation effect
| Hypothesis | Path relation | Point estimate | Product of coefficient | Bootstrapping | ||||
|---|---|---|---|---|---|---|---|---|
| Bias-corrected 95% CI | Percentile 95% CI | |||||||
| SE | Z | Lower | Upper | Lower | Upper | |||
| H1a | IA→I→PE | 0.988 | 0.704 | 4.728 | 1.758 | 2.623 | 2.035 | 3.687 |
| H3a | GP→CE→PE | 1.311 | 0.818 | 5.517 | 1.620 | 11.364 | 1.684 | 6.495 |
| H3b | GP→ME→PE | 0.636 | 1.364 | 4.406 | 0.168 | 3.265 | 3.698 | 5.879 |
| H3c | GP→PC→PE | 2.425 | 0.356 | 2.432 | 1.229 | 2.548 | 2.912 | 4.369 |
| H4a | CE→PC→PE | 2.139 | 0.803 | 3.237 | 1.847 | 8.546 | 0.652 | 3.068 |
| H4b | CE→PT→PE | 1.174 | 0.976 | 5.234 | 1.068 | 5.252 | -5.456 | 6.184 |
| H5a | ME→MT→PE | 0.824 | 0.937 | 6.455 | 3.135 | 6.523 | -5.662 | -0.415 |
| H5b | ME→PC→PE | 1.229 | 4.672 | 3.852 | -9.266 | -0.255 | -3.488 | 3.975 |
| H5c | ME→PT→PE | 2.141 | 5.364 | 0.331 | 1.059 | 15.595 | -6.952 | 7.084 |
From Table 6, it can be seen that the paths of audience personal attributes → interest level → communication effect, government policy → cultural environment →media environment → communication effect, government policy → communication content → communication effect, cultural environment → communication content → communication effect, and media environment → media technology → communication effect have significant mediation effects at the Bias-corrected 95% CI and at the Percentile 95% CI do not contain 0, indicating a significant mediating effect. This leads to the hypotheses H1a, H3a, H3b, H3c, H4a, and H5a are valid. Cultural Environment → Communication Talent → Communication Effect, Media Environment → Communication Content → Communication Effect, Media Environment → Communication Talent → Communication Effect in Percentile 95% CI are (-0.627, 6.184), (-3.488, 3.975), (-6.952, 7.084), respectively, and the interval contains 0, which indicates that the mediation effect of the path is not significant. This leads to hypotheses H4b, H5b, and H5c being invalid.
After controlling for cultural environment, media environment and communication content mediating variables, the government policy → communication effect path Bias-corrected 95% CI and at Percentile 95% CI do not contain 0, the mediating effect is significant, indicating that the direct effect of this path exists. It can be concluded that cultural environment, media environment and communication content play a partial mediating effect between government policy and communication effect.
After controlling for the mediating variable of interest degree, the audience personal attributes → communication effect path Bias-corrected 95% CI and in Percentile 95% CI both do not contain 0, the mediation effect is significant, indicating that the direct effect of this path exists. It can be concluded that interest level partially mediates the relationship between audience personal attributes and communication effects.
After controlling for the mediating variable of communication content, the cultural environment → communication effect path Bias-corrected 95% CI and in Percentile 95% CI do not contain 0, the mediation effect is significant, indicating that the direct effect of this path exists. It can be concluded that communication content plays a partial role in mediating the relationship between the cultural environment and communication.
After controlling for the mediating variable of media technology, the media environment → communication effect path Bias-corrected 95% CI and in Percentile 95% CI does not contain 0, the mediation effect is significant, indicating that the direct effect of this path exists. It can be concluded that media technology plays a partial role in mediating the relationship between the media environment and communication effects.
The results of the validation of the research hypotheses in this paper are shown in Table 7, and all the hypotheses in the full text passed the hypothesis test except H4b, H5b and H5c which were rejected.
Hypothesis conclusion
| Hypothesis | Path relation | Influence coefficient | Result |
|---|---|---|---|
| H1 | IA→PE | 0.162 | Support |
| H2 | I→PE | 0.149 | Support |
| H3 | GP→PE | 2.012 | Support |
| H4 | CE→PE | 1.090 | Support |
| H5 | ME→PE | 0.332 | Support |
| H6 | MC→PE | 0.175 | Support |
| H7 | PC→PE | 0.932 | Support |
| H8 | PT→PE | 0.253 | Support |
| H1a | IA→I→PE | 0.988 | Support |
| H3a | GP→CE→PE | 1.311 | Support |
| H3b | GP→ME→PE | 0.636 | Support |
| H3c | GP→PC→PE | 2.425 | Support |
| H4a | CE→PC→PE | 2.139 | Support |
| H4b | CE→PT→PE | 1.174 | Refuse |
| H5a | ME→MT→PE | 0.824 | Support |
| H5b | ME→PC→PE | 1.229 | Refuse |
| H5c | ME→PT→PE | 2.141 | Refuse |
The mechanism of digital dissemination of red culture can be summarized as three types: first, the dissemination of red culture at the individual level. Different types and attributes of the youth audience in contact with the ideological and political education of the red culture will have different degrees of interest, thus affecting the depth and breadth of the digital red culture in the dissemination of the youth audience. Second, the social level of red culture dissemination. Government policy is responsible for planning and conceptualizing the future direction and blueprint of the digital dissemination of red culture, while the cultural environment and media environment will have a greater impact on the content and form of the current digital dissemination of red culture, thus affecting the final dissemination effect. Third, the communication process in red culture. Media technology, communication content, and communication talents are the elements for implementing digital communication in Red culture. Red culture communication talents use digital media technology to encode red culture images, text, audio, video, etc. In cyberspace, the audience decodes interactively, which builds up an interactive platform for the subject and object of digital communication in red culture. With the help of digital media, all kinds of subjects in the red cultural communication activities express the red cultural information, continuously expand the scope of red cultural digital communication, and improve the effect of red cultural digital communication.
This paper constructs a structural equation research model based on the characteristics of red culture and its digital communication, explores the influencing factors of digital communication of red culture in youth ideological and political education, and clarifies the operation mechanism of digital communication of red culture in conjunction with the findings of empirical research.
The proportion of male and female respondents to the questionnaire is 48.99% and 51.01%, respectively, which is basically balanced. 84.72% of the respondents are under 30 years old, 83.82% have a bachelor’s degree or above, and more than half of the respondents have an average monthly income of less than 3,000 yuan. The top three ways for audiences to access digital red culture are short videos, digital museums’ WeChat small programs or APPs, and red culture-related documentaries. More than half of the respondents said they were most impressed by art and music.
The p-values of the influencing factors such as personal attributes of the audience, interest in red culture, government policies, cultural environment, media environment, media technology, communication content, and communication talents, and the communication effects are all significantly correlated with each other with p-values less than 0.01.
Assuming that the standardized path coefficients of H1, H2, H3, H4, H5, H6, H7 and H8 are 0.162, 0.149, 2.012, 1.090, 0.332, 0.175, 0.932, 0.253, respectively, with the P-values of all of them being less than 0.05, and assuming that the corrected skewness and percentile of H1a, H3a, H3b, H3c, H4a, H5a confidence intervals do not contain 0, and H4b, H5b, H5c percentile confidence intervals contain 0. It is assumed that H1a, H3a, H3b, H3c, H4a, H5a are valid, and it is assumed that H4b, H5b, H5c are not valid.
This research was supported by the 2024 Shanxi Province Higher Education Philosophy and Social Sciences (Ideological and Political Education Special Project): Research on the Integration of Red Cultural Resources into the Practice of Ideological and Political Education in Colleges and Universities in the Era of Integrated Media (Project Number: 2024zsszsx189);
Special Research Project for Counselors at Fenyang College, Shanxi Medical University: Research on the Integration of Red Cultural Resources into the Practice of Ideological and Political Education in Colleges and Universities in the Era of Integrated Media (Project No: SZ2024001).
Comprehensive Reform and Boutique Construction Project for Improving the Quality of Ideological and Political Work in Shanxi Province’s Universities in 2025: “Time Notes, Heart Mail Express” - Research on the Practice and Innovation of Home Letter Culture Education for New People in the Era.(Project approval date: December 30, 2024)