Information Diffusion Model Research Articles

Multi‐UAV Cooperative Search for Moving Targets With Impaired Communication Using Improved Gray Wolf Optimizer

The study investigates the problem of collaborative target search by multiple unmanned aerial vehicles (UAVs) under the condition of communication information corruption. The problem involves the influence of target movement and environmental obstacles on the update of the UAV’s local target probability map (TPM), as well as communication information corruption among UAVs due to packet loss and resulting local information inconsistency. The objective is to efficiently plan paths for the UAV swarm to discover more targets. To address the above issues, this paper proposes the following methods. Firstly, an information diffusion model is introduced to simulate the TPM changes caused by target movement and the discovery of obstacles based on a two‐dimensional Gaussian distribution, thereby correcting the real‐time target information held by UAVs. Secondly, a radial basis function neural network (RBFNN) is employed to recover the corrupted information, and a weighted averaging method is used to fuse the information from multiple UAVs, achieving consensus among the UAVs. Lastly, the original gray wolf optimizer (GWO) is enhanced by incorporating strategies such as Levy flight and the nonlinear convergence factor. Subsequently, the improved GWO is integrated with the model predictive control (MPC) for UAV trajectory planning, enabling a more efficient search for optimal paths. Experimental results demonstrate that the proposed information recovery method outperforms the compared methods by 24.7% in terms of performance. The proposed comprehensive search approach shows higher efficiency in searching for more targets within a specified time, and it also exhibits advantages in terms of area coverage and other aspects.

Study on Optimizing the Communication Path of Hunan Sports Culture Based on the Information Diffusion Model

Abstract This paper takes the dissemination of Hunan sports culture as an example and analyzes its characteristics and development process in depth. By combining the continuous bag-of-words model and the Word2Vec model constructed by Skip-gram algorithm, this study determines the word vectors of the text data. It introduces the LDA theme model to reveal the implicit theme information in the document set. Based on this, a theme model of Hunan sports and cultural communication that mimics the spread of infectious diseases was constructed. By analyzing the information and comments collected from 2016 to 2020, this study identifies the theme keywords and explores the intensity change, sentiment tendency and drift path of different themes. The results showed that “spiritual and educational values” had the most remarkable combined intensity during the study period, with an average of 1.09, while “social values” increased over time, reaching a maximum intensity of 1.14 in 2020. A more pronounced negative sentiment characterized 2016-2018, 2018-2020 was marked by a more pronounced negative sentiment, and 2018-2020 by a more pronounced negative sentiment. Emotions were more significant, while positive and neutral emotions were more prominent in 2018-2020. Based on these findings, it is recommended to increase economic development and promote the spiritual connotation and educational value of Hunan sports culture through diversified communication to enhance the city’s soft power.

Blowing Seeds across Gardens: Visualizing Implicit Propagation of Cross-Platform Social Media Posts.

Propagation analysis refers to studying how information spreads on social media, a pivotal endeavor for understanding social sentiment and public opinions. Numerous studies contribute to visualizing information spread, but few have considered the implicit and complex diffusion patterns among multiple platforms. To bridge the gap, we summarize cross-platform diffusion patterns with experts and identify significant factors that dissect the mechanisms of cross-platform information spread. Based on that, we propose an information diffusion model that estimates the likelihood of a topic/post spreading among different social media platforms. Moreover, we propose a novel visual metaphor that encapsulates cross-platform propagation in a manner analogous to the spread of seeds across gardens. Specifically, we visualize platforms, posts, implicit cross-platform routes, and salient instances as elements of a virtual ecosystem - gardens, flowers, winds, and seeds, respectively. We further develop a visual analytic system, namely BloomWind, that enables users to quickly identify the cross-platform diffusion patterns and investigate the relevant social media posts. Ultimately, we demonstrate the usage of BloomWind through two case studies and validate its effectiveness using expert interviews.

A Multi-Layer Information Dissemination Model and Interference Optimization Strategy for Communication Networks in Disaster Areas

A Multi-Layer Information Dissemination Model and Interference Optimization Strategy for Communication Networks in Disaster Areas

A Study of Digital Communication Paths in Contemporary Politics and Marxist Thought

Abstract In the context of digital technological change and media convergence, how to quantitatively analyze the digital communication path of contemporary politics and Marxist thought has become a new problem to be solved. The objective of this paper is to create a model for analyzing the digital communication path of political information and Marxist thought. The degree correlation in the social network algorithm is used to analyze the correlation between the information nodes of contemporary politics and Marxist thought, and the clustering coefficients are used to predict the behavior and evolution of the nodes in the dissemination network. The dissemination model of contemporary politics and Marxist ideology can be explored by combining the infectious disease information dissemination model on the network platform. After the construction has been completed, the model is employed to evaluate the relevant information of a network platform. The early stages of the spread of political and Marxist-related information resulted in 180,000 crowd contacts becoming information exposers and quickly reaching the peak point. The peak point of 119,800 people is quickly reached when both intentional and unintentional communicators of political messages increase. Node density reaches 0.94 and then declines roughly 24 hours after the political message is released. The model employed in this paper is capable of effectively analyzing the digital dissemination path of politics and Marxist ideology and providing a reference for exploring the digital dissemination of political information.

Extracting the diffusion dynamics of crisis information on online social networks: Model and application

Disaster mitigation greatly benefits from the diffusion of crisis information. To learn about the diffusion dynamics of crisis information on online social networks, this paper puts forward a crisis information diffusion model based on population dynamics and further analyses its parameters, such as ordinary users’ average number of followers, the number of potential audience members who might spread the crisis information, the forwarding probability for each audience member and the attenuation speed of the information based on real data from Sina Weibo. In addition, a method for the prediction of crisis information diffusion is proposed and verified on the basis of this model. The results show that this model could describe and predict well the diffusion process of crisis information on online social networks, enabling relevant departments to develop appropriate strategies for crisis information diffusion.

Optimization of network flows for rural extension of fruit and vegetable agricultural technologies

Abstract This paper focuses on the rural promotion of fruit and vegetable agricultural technology and proposes a network flow optimization model based on linear programming for the diffusion of fruit and vegetable agricultural technology. Based on the Bass model, it describes the process of natural growth of network users and the word-of-mouth effect among them. Fruit and vegetable agricultural technology diffusion in real social networks is fitted and predicted by the social network information dissemination model, and the network flow problem of fruit and vegetable agricultural technology promotion is optimized using linear programming equations. Based on this basis, the algorithm designed in this paper and the effect of rural promotion of fruit and vegetable agricultural technology are analyzed with relevant data. The results show that the coefficient of the variable of the number of promotion times in the behavior of agrotechnology promotion is 0.064, which has a significant positive effect on the evaluation of the rural promotion performance of fruit and vegetable agricultural technology, indicating that increasing the number of agricultural technology training and enriching the content of agricultural technology promotion will help to improve the evaluation of the rural promotion performance of fruit and vegetable agricultural technology by farmers. The network flow optimization model constructed in this paper can enable farmers to master more modern fruit and vegetable agricultural technology to meet the needs of modern production of fruit and vegetable agriculture so as to improve the level of local fruit and vegetable agricultural development.

Research on the Construction of University Cultural Brand IP Driven by Network Cloud Platform Technology

Abstract Campus culture brand IP, as the soft power in the construction of university brand culture, has become an important material carrier for the inheritance and dissemination of university brand culture. In the cloud platform technology, we are using an information diffusion model to explore the diffusion degree and influence of college culture brand IP information on the network platform. The dissemination process of cultural brand IP information is examined from the point of view of sharing information resources in colleges and universities. Construct a competitive information dissemination system based on the user nodes of online social networks and the interrelationship between users. Promote the dissemination and diffusion of university cultural brand IP information on online social networks using a data-driven approach. The results show that: k value is 0.12, the promotion effect of college culture brand IP is 2.59621e+04, and the relative risk index is 0.354264. Within 0-6 hours, the maximum number of IP views reaches 34,000 times, which indicates that the authority of the college platform and the information diffusion model can improve the diffusion of college culture brand IP.

The dynamic coupling mechanism of information and epidemic propagations considering individual mobility in two-layer network framework

The epidemic had taken massive hurt on human beings for their lethal viruses and rapid spread, such as the outbreak of Corona Virus Disease 2019 (Covid-19). How to control the virus spreading came to be a tough question and drew a lot of research attentions at that time. By the empirical data analysis from Shanghai China, we find information diffusion is co-evolving with epidemic spread, and vice versa. In order to reveal the coupling mechanism of epidemic spread and information diffusion, or the influencing factors on epidemic spread, we present a two-layer network framework to investigate the coupling mechanism of information diffusion and epidemic spread, and discuss the influencing factors. Thus, from the perspective of considering individual behaviors (such as individual mobility), a coupling propagation model of information diffusion and epidemic spread in two-layer network framework is proposed by dynamic equations. With the theoretical and numerical analysis, it is found epidemic spread might be influenced by epidemic itself mechanism and individual mobility indicated by mobility frequency and range to a certain extent from the micro perspective. Moreover, the role of individual mobility in promoting or delaying epidemic spread depends on the distribution of epidemic network. While from the macro perspective, it is found that promoting information diffusion in social networks could reduce the epidemic spread scales effectively by calculating the epidemic threshold and comparing with Monte Carlo (MC) simulation experiments. In addition, the global control strength from government or social organizations is also a key factor for reducing epidemic spread. Results in this work provide some reasonable and practical strategies for management on epidemic prevention and control in future.

Drivers of social influence in the Twitter migration to Mastodon

The migration of Twitter users to Mastodon following Elon Musk’s acquisition presents a unique opportunity to study collective behavior and gain insights into the drivers of coordinated behavior in online media. We analyzed the social network and the public conversations of about 75,000 migrated users and observed that the temporal trace of their migrations is compatible with a phenomenon of social influence, as described by a compartmental epidemic model of information diffusion. Drawing from prior research on behavioral change, we delved into the factors that account for variations of the effectiveness of the influence process across different Twitter communities. Communities in which the influence process unfolded more rapidly exhibit lower density of social connections, higher levels of signaled commitment to migrating, and more emphasis on shared identity and exchange of factual knowledge in the community discussion. These factors account collectively for 57% of the variance in the observed data. Our results highlight the joint importance of network structure, commitment, and psycho-linguistic aspects of social interactions in characterizing grassroots collective action, and contribute to deepen our understanding of the mechanisms that drive processes of behavior change of online groups.

A Study on the Presentation and Communication Influence of Shaanxi Regional Culture in Public Service Advertisements from the Perspective of Social Network Analysis

Abstract This paper describes the dynamic propagation process of the influence of public service advertisements (PSAs) using the information dissemination model and proposes a click probability function by modeling the click rate of advertisements, which is solved by a heuristic method. The EPR advertisement recommendation algorithm is selected to simulate the push process of the advertisement, and the experimental performance is analyzed. Analyze the presentation of Shaanxi regional culture and the network mobilization mechanism model of enterprise public service advertisement, predict and analyze the click rate of public service advertisement broadcasting, and emphasize the trust analysis of the audience. Variables such as the number of effective viewing of advertisements, the number of link clicks, the number of likes, and the amount of placement are selected to carry out descriptive analysis and correlation analysis of the effect of PSAs on Shaanxi regional culture. From the correlation coefficient matrix, it can be seen that the correlation coefficients between the explanatory variables take smaller values and are at the level below 0.11, and the number of likes has significant positive correlation coefficients with the indicators of advertisement effect at each stage. Thus it can be verified that the social attributes of advertisements play a positive role in the effect of advertisements.

Combining the Information Diffusion Model for the Propagation of Zhouyi Ideology in the New Era

Abstract This paper examines the moral edification ideas in Zhouyi and looks at the contemporary value of Zhouyi ideology and ideology. The UAU-SIS multiple network communication model is constructed, and the information radiation model between cyberspace and real space is proposed, which has a positive impact on the dissemination of Zhouyi ideology. The Master differential equation of the degree distribution of spatial topological structure is established to provide a basis for the dissemination of information related to Zhouyi ideology. Analyze the communication carriers of Zhouyi thought and improve the communication effect of Zhouyi thought in the new era by combining it with information diffusion technology. Simulation experiments are used to examine the feasibility and performance of the proposed algorithm. Investigate the influence of Zhouyi’s thought dissemination on citizens’ moral education consciousness. The experiment shows that the diffusion range of the algorithm is improved from 100 to 600 after 16 iterations, and the increased speed decreases to 4879.13s, the dissemination effect is better, and the algorithm is feasible. The scores of 6 evaluation indexes of students’ moral edification are 0.76, 0.93, 0.71, 0.63, 0.91, and 0.53. The overall level is good, and there is still room for improvement in the awareness of moral edification. It can be seen that the spread of Zhouyi thought has a beneficial effect on the citizens’ consciousness of moral enlightenment.

A novel regularized weighted estimation method for information diffusion prediction in social networks

In recent years, social networks have become popular among Internet users, and various studies have been performed on the analysis of users’ behavior in social networks. Information diffusion analysis is one of the leading fields in social network analysis. In this context, users are influenced by other users in the social network, such as their friends. User behavior is analyzed using several models designed for information diffusion modeling and prediction. In this paper, first, the problem of estimating the diffusion probabilities for the independent cascade model is studied. We propose a method for estimating diffusion probabilities. This method assigns a weight to each individual diffusion sample within a network. To account for the different effects of diffusion samples, several weighting schemes are proposed. Afterward, the proposed method is applied to real cascade datasets such as Twitter and Digg. We try to estimate diffusion probabilities for the independent cascade model considering the continuous time of nodes’ infections. The results of our evaluation of our methods are presented based on several datasets. The results show the high performance of our methods in terms of training time as well as other metrics such as mean absolute error and F-measure.

Analysis of Teachers’ Discourse in the Digital Platform Mode of College English Teaching Based on the Information Diffusion Model

Abstract This paper utilizes the information diffusion mechanism of the information extension model, which can act on the influence of students in the process of university English teaching to the information extension model to the diffusion ability that English information has. It examines the level of student activity and English information coverage in university English teaching and discusses the use of the information extension model in English teaching. According to the objectives of university English teaching, the functional requirements of the university English teaching platform are analyzed, the university English teaching platform based on the information diffusion model is designed through big data technology, and the English teaching platform combined with the information extension model is analyzed in an example study. The results show that on the model simulation analysis, the performance of this paper’s model is better than the User Rank model and UI-LR model when mining less than 30 information extensions. In the analysis of teachers’ discourse, the speech rate of teachers in the university English teaching platform is mainly concentrated in the range of 140-149 syllables/minute and 150-159 syllables/minute, and only one teacher’s speech rate exceeds 170-179 syllables/minute. This study has the potential to enhance students’ understanding of teachers’ discourse and establish a solid platform for communication between teachers and learners.

APPLICATIONS OF SOCIAL NETWORK ANALYSIS IN PROMOTING CIRCULAR ECONOMY: A LITERATURE REVIEW

Circular economy (CE) is a sustainable alternative to tackle global challenges like climate change, waste, and pollution. The relations, perceptions and behaviors of stakeholders in circular economic activities may form barriers that hinder the circular transition. The promotion of CE requires investigating the interactions and information flow between CE stakeholders from a network perspective. This study revisits the applications of social network analysis (SNA) in promoting CE. Related concepts of CE and the research contents of SNA are reviewed. A bibliometric analysis is conducted to provide a bird’s eye on the research status and trend. On this basis, we summarize the challenges of promoting CE and refine specific problems, around which we review the research status of network modeling methods and statistical measures, information diffusion models, mining methods of perceptions, and social influence analysis. This study outlines the pathways through which SNA contributes to promoting CE, such as through revealing the relational structure and characteristics of stakeholders, forming and changing perceptions of stakeholders, improving behaviors of stakeholders, and examining the development of CE. The lessons learned from the review and future prospects are extensively discussed in combination with the features of the information age from both theoretical and practical perspectives.

Exploring the Research on Media Communication Strategies of Public Welfare and Charity Organizations in the Context of Social Governance Innovation

Abstract In the context of social governance innovation, the integration and sharing of information are studied through the construction of an information-sharing platform. The process of interpreting the evolution of new media information dissemination includes analyzing the characteristics and laws of information dissemination on various platforms. Based on the existing scale of public welfare charities, the kinetic evolution equation of the public welfare information dissemination model is established to describe the dissemination process of public welfare information and its influencing factors. The impact of media intervention on the final scale of public welfare information dissemination is analyzed using the collected Facebook dataset as the background, and it is found that the higher the media credibility is at t = 4, the public welfare information attracts media attention. After the release of public interest information, the immunity node began to show a gradual upward trend, reaching a maximum of 1.0. Indicating that after the media release of public interest information, the final scale of dissemination of public interest information increases.

Linguistic Characteristics and Stylisation of Korean Cinema Based on the Social Network Analysis Method

Abstract Korean movies have consistently produced exceptional works that have triggered discussions and spread on social networks in recent years. In this paper, we take the movie language dissemination characteristics in social networks as an anchor point and combine the scale and structure of social networks to improve on the IC model to obtain a movie information dissemination model. This network model and the information cascade tandem are selected as the core of density peak clustering, and improvements are made for the updating rules as well as the propagation order of the multi-strategy labeling algorithm in the DCN algorithm. The characterization of movie language propagation in social networks is completed by using an improved algorithm with a multi-labeling idea. The overall stylistic evolution of Korean movies is examined, and then different language feature styles are compared according to social propagation. In the movie Memories of Murder, at 32 minutes and 23 seconds, which shows a rainy night on a muddy land and conveys the hardship of the protagonist’s situation through visual language, the propagation heat reaches 10.52. Similar to this sentence, the movie depicts a rainy night at 63 minutes and a crime scene at 108 minutes, with the propagation heat of the visual language reaching 19.48 and 23.48, respectively. Based on the propagation analysis of the social networks, the accurate capture of the unique impression of the movie language among the audience.

Integration Development of Civic Education and Student Management in Colleges and Universities Based on Information Diffusion Modeling

Abstract This paper utilizes the idea of information diffusion to model the diffusion effect of information on civic and political education and categorizes the elements for the impact of the civic and political information diffusion system from the three levels of dissemination, acceptance and control. In order to verify the validity of the Civic and Political Information Diffusion Model, manipulative tests and empirical analysis are carried out. The results show that the breadth and depth of the Civic and Political Information Diffusion Model’s manipulability test Sig are significant. They are both less than 0.05, with significant differences. The specific factors affecting the integration and development of civic education and student management can be analyzed more intuitively from the three levels of dissemination, acceptance, and control. This shows that the use of the information diffusion model can provide an effective research direction for the development of the integration of civic education and student management in colleges and universities and lay a good foundation for the cultivation of high-level talents adapted to the development needs of the new era.

Application of Digital Health Concepts in Dance Culture Dissemination and Promotion Based on Predictive Modelling of Information Dissemination

Abstract The purpose of this paper is to analyze the dissemination effect of digital health concepts in dance culture by constructing a prediction model for dance culture information dissemination. It focuses on analyzing the main paths and forms of Internet+dance culture dissemination and constructing the cultural dissemination process of Internet+dance health. The LSTM method is used to extract the states in information dissemination, and the dissemination characteristics of digital health in dance culture are deduced by analyzing the characteristics of the information dissemination sequence. The association between digital health concepts and dance culture dissemination was determined through the trajectory characteristics of information dissemination. The results show that the spreading range of the four types of models rises in an upward trend and is faster when the spreading time round is in the interval of (0,125). The spread range in models in the (150,300) interval is generally higher than the SI model and SEI model. The factor value of whether the video is top or not affects the amount of playback is 0.771***, and the factor value of whether it carries a topic or not is 0.051.

Regional Risk Assessment for Urban Major Hazards Using Hybrid Method of Information Diffusion Theory and Entropy

Urban regional risk is a complex nonlinear problem that encounters insufficient information, randomness, and uncertainty. To accurately assess the overall urban risk, a regional risk assessment model for urban public safety was proposed by using the information diffusion theory. The entropy theory was employed to optimize the information diffusion model to reduce the uncertainty. A framework of urban regional risk assessment model based on information diffusion and entropy was constructed. Finally, a case study of Hangzhou city in China was presented to demonstrate the performance of the proposed method. Results showed that the proposed method could successfully estimate the urban regional risk of Hangzhou city. The risk levels and probabilities of different hazard indicators were basically consistent with reality. The hazards with respect to industrial and mining accidents and road traffic accidents were extremely serious. More than 80 deaths from industrial and mining accidents would occur almost every 3 years, and more than 400 deaths of RTA would occur almost every 2.6 years. Moreover, centralized intervals of the risk level associated with five hazards were found, where urban risks were more likely to happen and had higher vulnerability. It could provide guidance for the government’s urban safety management and policy-making.