A Structural Hole-Based Approach to Control Public Opinion

Finding structural hole spanners based on community forest model and diminishing marginal utility in large scale social networks

Opinion dynamics models based on the multi-agent method commonly assume that interactions between individuals in a social network result in changes in their opinions. However, formation of public opinion in a social network is a macroscopic statistical result of opinions of all expressive individuals (corresponding to silent individuals). Therefore, public opinion can be manipulated not only by changing individuals’ opinions, but also by changing their states of expression (or silence) which can be interpreted as the phenomenon “spiral of silence” in social psychology. Based on this theory, we establish a “dual opinion climate” model, involving social bots and mass media through a multi-agent method, to describe mechanism for manipulation of public opinion in social networks. We find that both social bots (as local variables) and mass media (as a global variable) can interfere with the formation of public opinion, cause a significant superposition effect when they act in the same direction, and inhibit each other when they act in opposite directions.

Tripartite game analysis of online public opinion evolution in major epidemics in the context of life sciences.

Social media platforms have become a major tool for information dissemination, political communication, and political civic discussion nowadays. However, the prompt transmission of fake news and misinformation on Facebook has raised severe concerns about public trust and opinion formation. This study examines the proliferation of fake news on Facebook and its impact on individuals' trust levels and perception in Punjab, Pakistan. By employing Agenda-Setting Theory and the Two-Step Flow Model of Communication, the research conceptualizes misinformation as a mediated influence that shapes the prominence of an issue and public attitude through opinion leaders and AI-driven visibility. A quantitative research design was employed using a random sampling survey administered to 100 respondents, including faculty and administrative staff members and students of the University of Gujrat (Hafiz Hayat Campus), and individuals from different educational backgrounds from different areas of Punjab, Pakistan. The study further integrates Artificial Intelligence (AI)-based verification of content/news to cross-check and identify patterns in misinformation dissemination, thereby linking advanced technological intervention with Communication Theory. The findings of this research study reveal a significant relationship among exposure to fake news on Facebook, changes in opinion formation, and reduced trust. The study enriches the current body of literature on social media, Public Opinion, Misinformation, Agenda-Setting, and Digital Trust in developing countries.

In the conditions of digitalization, which has penetrated all spheres of human life and society, artificial intelligence (AI) and ultra-precise neural networks influence our thinking and form consumer demand and loyalty. Modern AI applications cover all the essential areas of activity: education, manufacturing, marketing, management, law, medicine, and e-commerce. The study aims to build a methodology for analyzing the influence of public opinion in social networks, particularly micro and nano influencers, through AI and machine learning on the effectiveness of companies' marketing activities. The authors studied the stages of consumer interaction with marketing profits and highlighted the role of AI technologies in each of them. They showed that public opinion was the main driving force for effective sales of products on the Internet. Based on empirical data, a strong direct relationship was found between the number of influencers and the dynamics of marketing profit: it was revealed that the correlation coefficients between the marketing profit index and the number of micro and nano influencers were 0.86–0.99 in all surveyed companies implementing AI technologies, regardless of the market niche. Based on the expert method, the company's marketing system is investigated. An integral indicator of its effectiveness is introduced, consisting of sub-indices of analysis, diffusion and marketing information management. The authors considered the factors of profit from marketing activities of five companies actively implementing AI in brand promotion, including those using the leadership opinions of influencers. The applied value of the developed methodology is the possibility of using it to construct Internet marketing strategies by companies. By permanently monitoring the relationship between the marketing profit index and the degree of brand popularization in social networks, companies can manage sales at all stages of consumer communications, optimizing the costs of influencers promoting products on different social platforms. The prospects for further research are to study the relationship between the degree of interactivity of the influencer with the audience, the content posted by it with the conversion rate and sales volumes; grouping and identification of influencers based on the clustering method.

The authors use primary archival records from Lyndon Johnson's presidency to rethink realist theory in international relations concerning leadership of public opinion in foreign policy. Much as the realists expect, Johnson pursued a strategy of opinion leadership that was intended to direct public opinion as he and his administration reacted to the country's international position. Using archival evidence and statistical analysis, the authors examine the relationship between public opinion information that was privately channeled to the White House and several measures of Johnson's behavior including presidential statements and military decisions about bombing and troop deployments. They find that Johnson was unresponsive to public opinion and also generally ineffective in directing public opinion. They conclude that realists' analysis of opinion leadership in representative democracies is inadequate and can lead to impractical prescriptions. What is needed is a theory of foreign policy making that incorporates the complexities of opinion leadership.

Evolution mechanism and influencing factors of multidimensional public opinion dissemination from the perspective of game theory

In this paper, an improved Susceptible- Infected-Susceptible (SIS) epidemic spreading model is proposed in order to provide a theoretical method to analyze and predict the spreading of diseases. This model is based on the following ideas: in social networks, the contact probability between nodes is decided by their social distances and their active degrees. The contact probability of two indirectly connected nodes is decided by the shortest path between them. Theoretical analysis and simulation experiment were conducted to evaluate the performance of this improved model. Because the proposed model is independent of the network structure, simulation experiments were done in several kinds of networks, namely the ER network, the random regular network, the WS small world network, and the BA scale-free network, in order to study the influences of certain factors have on the epidemic spreading, such as the social contact active degree, the network structure, the average degree, etc. This improved model provides an idea for studying the spreading rule of computer virus, attitudes, fashion styles and public opinions in social networks.

Opinion leaders on the internet play an important role in promoting the formation of online public opinion, which can influence the direction of public opinion. In this paper, we use social network analysis and content analysis to recognize the opinion leaders of online communities. First of all, we propose Eight Degree attribute indexes based on the characteristics of opinion leaders. Then, we construct an attribute matrix of the topic participants, and use the comprehensive evaluation to recognize opinion leaders. Finally, we divide the opinion leaders into the crucial active figure and the important position figure; we can also explore the potential opinion leader deeply by deleting the opinion leaders. The theoretical significance and practical value of this method have been demonstrated by a case study.

The Asian social networks are dominated by the society’s collectivist culture, and this interestingly introduces an influence mechanism aided by word-of-mouth and opinion leaders. An opinion leader can help to generate and shape other people’s opinion and achieve a high information spread on any topic. In this work, a modified spider monkey optimization based opinion leader detection approach is proposed. Firstly, we employ the modified node2vec graph embedding to generate the lower dimensional vectors which act as the initial features for the nodes in a typical Asian social network. Next, the entire population is broken down into several groups using the k-means++ algorithm where the number of clusters is equal to the number of opinion leaders to be selected. The local and global leaders are chosen by using the coordinates of the cluster centres of these clusters. The coordinates of the centroids of the clusters are then used to detect the local and global leaders in the network. The local leaders then form the seed set of opinion leaders for the network. The positions of the nodes in the network, including the local and global leaders, are updated over a number of iterations. At the end of these iterations, the seed set generating the maximum influence forms the set of opinion leaders in the network. We test our proposed approach using the popular information diffusion and cognitive opinion dynamics (COD) models. We perform intensive experiments on several real-life social networks based on various performance metrics. The results obtained reveal that the proposed approach outperforms several existing techniques of opinion leader detection.

To the Editors:We read with great interest the report of the Results of the National Institute of Mental Health Collaborative HIV/Sexually Transmitted Disease Prevention Trial of a Community Popular Opinion Leader (C-POL) Intervention.1 This trial tested whether a well-described and effective commun

Social networks are ubiquitous, which has been one of the important topics of many scholars. With the rapid development of information technology in recent years, people's social platforms are not limited to offline, and online social networks have gradually become an indispensable part of our lives. However, there is still a lack of research on the differences between online and offline social networks. Therefore, this paper probes into the differences between online and offline social network information dissemination by collecting data from online and offline double-layer coupled networks, and comparing and analyzing the data. Research shows that there are some differences between online and offline social networks in the law of information dissemination, which will have a certain impact on real life. Therefore, three suggestions are put forward: 1. At the initial stage of promotion, there are few audience groups, so offline methods can be adopted. With the expansion of information dissemination scope, gradually turning to online promotion, the best promotion effect will be achieved at the fastest speed. 2. The speed and effect of information dissemination can't be ignored for people who have no value in social network information dissemination. 3. Based on the complexity of the public opinion information dissemination network, users need to constantly cultivate their ability to identify information, the management of major social platforms earnestly perform their regulatory responsibilities, and the relevant functional departments of the government gradually establish a public opinion guidance mechanism. If joint efforts can be formed, the public opinion prevention and control effect will be more significant.

网络舆情的传播主体在网络舆情的发生、发展和演化过程中具有重要作用，舆情的应对也离不开网络传播主体。网络意见领袖作为活跃主体，与网络舆情的演化有着密切的联系。方法层面有必要开展基于网络舆情传播主体的分类研究，掌握活跃主体的形成及在舆情传播中的作用；技术层面有必要基于信息分析方法研究网络意见领袖的发现，证明社会网络分析技术能有效用于舆情主体的挖掘过程及其量化分析。实证展示舆情主体的挖掘过程及其信息分析方法的应用。 The main body of the network public opinion plays an important role in the occurrence, development and evolution of the network public opinion. Network opinion leaders as the active agent, have a close relationship with the evolution of the network public opinion. For the method level, it is necessary to carry out the classification based on the main body of network public opinion dissemination and to master the formation and role of active subject in the spread of public opinion; For the technical level, it is necessary based on intelligence analysis method to study network opinion leaders’ findings to prove that social network analysis technology can be effectively used for the main public opinion mining process and quantitative analysis. There are real evidences in the paper to demonstrate the mining process of the main body of public opinion and the application of information analysis method.

In the context of the new era, teachers and students in colleges and universities, as well as the general public, rely more on the Internet and social media to obtain news, express their opinions, and share information, and the dissemination of public opinion events in colleges and universities is not only related to the physical and mental health of teachers and students but also to the reform and development of colleges and universities. In this study, we took campus public opinion events as the main research object in which we selected three recent campus public opinion events to be analyzed. The public opinion data used in the research was collected from Weibo social media platforms. Firstly, we analyzed the dissemination cycle and regional dissemination patterns of a college food safety public opinion hot event through the popularity and regional distribution of public opinion data, thus revealing its formation and evolution patterns. Secondly, the LDA topic mining method is used to mine the themes of the three hot public opinion events, and then analyze the hot factors of the dissemination of each public opinion event from the massive public opinion data. This is crucial for the management department to grasp the dynamics of public opinion. Then, we used the SKEP sentiment classification method to analyze the emotional factors of the public opinion data of the three events to obtain the overall public opinion sentiment situation of the events. Finally, based on the characteristics of time, region, and gender, the evolution and diffusion rules of public topics and emotional distribution under different types of events are analyzed. The precision of the analyses associated with this paper may be limited to the effects of current mainstream as well as state-of-the-art analytical models. The analysis methods and conclusions in this paper provide a scientific theoretical basis and improvement measures for campus public opinion management, which helps to enhance the level of campus public opinion management and safeguard campus stability and public order.

Opinion leadership has been the subject of numerous studies, in areas ranging from politics to marketing. The present study examines a new measure to identify opinion leaders (the personality strength scale developed by the Allensbach Survey Center in Germany) and combines it with modern social network analysis. An application of this scale to agenda setting and public opinion research is the main point of concern in this study. The findings of the study (a survey of a representative sample of 900 adults in Germany) suggest, that the Strength of Personality Scale fits a more sophisticated characterization of opinion leadership which is based on modifications of the original opinion leader concept. Moreover, the results indicate that people with high personality strength have social networks of great range and are especially active in interpersonal communication. They use print media very frequently and know very well the actual topics and issues on which the mass media report. Although people with high personality strength are able to exactly assess the true climate of opinion, they hold distinct positions which differ from public opinion. In contrary, persons with low personality strength tend to adapt their opinions to the perceived climate of opinion.