Information Dissemination Behavior Research Articles

The Mechanism of Tendentious Information Dissemination in Cyberspace

Cyberspace has evolved into a hub for the dissemination of large amounts of tendentious information, posing significant challenges to the role of mainstream value information. As netizens’ are the main recipients of tendentious information, their personal cognition, attitude, and behavioral ability affect their willingness to re-disseminate information, making them an inalienable force in the promotion of information dissemination. Exploring the dissemination mechanism of tendentious information in cyberspace can help to understand the law of information dissemination and predict the trend of information diffusion, which is of great significance to maintaining information security and social stability. However, the existing research has overlooked the potential influence of the attribute characteristics of information in terms of content, and has failed to overcome the methodological constraints of traditional statistical analysis to accurately describe the variables and mechanisms influencing the dissemination of tendentious information at the cognitive level. Therefore, using structural equation modeling, we propose a research index system based on the Theory of Planned Behavior and the characteristics of tendentious information. To this end, confirmatory factor and model fitting analyses were conducted to develop a tendentious information dissemination mechanism model, which we validated through testing and comparative experiments. Path analysis revealed that Attitude Toward Dissemination, Information Dissemination Intention, and Information Dissemination Behavior are the main links in the information dissemination process. Moreover, Information Sentiment Orientation was found to strongly promote the dissemination of tendentious information, while Subject Norm of Dissemination had a minor inhibiting effect.

Dynamic evolutionary analysis of opinion leaders’ and netizens’ uncertain information dissemination behavior considering random interference

Dynamic evolutionary analysis of opinion leaders’ and netizens’ uncertain information dissemination behavior considering random interference

Information dissemination behavior of self-media in emergency: Considering the impact of information synergistic-hedging effect on public utility

In the context of emergency, besides handling the incident itself, controlling public opinion is also crucial. Self-media, as a crucial channel for the public to access information, controlling its dissemination behavior is key to public opinion management. Given the complexity of self-media information dissemination, we propose an evolutionary model for social media information dissemination behavior based on complex network theory and evolutionary game theory. Firstly, aiming at the synergistic and hedging effects of information dissemination, we use the utility function to depict the public's information demand. Next, based on the public's information needs, evolutionary game theory is introduced to analyze the information dissemination behavior between two self-media entities. Lastly, we map the dissemination behavior of self-media onto network space, analyzing the information propagation behavior of self-media within a complex network. The study shows that the probability of self-media disseminating positive information increases with the rise of the positive information synergistic effect and decreases with the increase of the negative information synergistic effect. When positive and negative information coexists, the dissemination behavior of self-media depends on the influence size of positive and negative information. With the improvement of government credibility, the probability of self-media disseminating positive information decreases slightly at first, and then increases rapidly. When the government's penalties increase, the probability of self-media disseminating positive information quickly rises. The changes in noise intensity have an uncertain impact on the positive information dissemination behavior of self-media. Compared with other factors, self-media is more sensitive to government credibility and punishment.

Exploring users' content creation and information dissemination behavior in social media: The moderating effect of social presence

Users' personality traits reveal different social media behavior characteristics. In order to explore the intrinsic relationships between personality traits and social media behavior, this study analyzes the influence of users' personality traits on social media content creation and information dissemination behavior, as well as the moderating effect of social presence. We collect users' personality data via questionnaires, crawl social media behavior data of samples from social media sites, and then establish regression models to test the research hypotheses. The results show that extraversion has a positive impact on content creation and information dissemination behavior, conscientiousness has a negative impact on content creation behavior, openness and agreeableness have no significant impact on social media behavior, and social presence has significant moderating effects on the relationships between personality traits and social media behavior.

Influence of information attributes on information dissemination in public health emergencies

When public health emergencies occur, relevant information containing different topics, sentiments, and emotions spread rapidly on social media. From the cognitive and emotional dimensions, this paper explores the relationship between information attributes and information dissemination behavior. At the same time, the moderating role of the media factor (user influence) and the time factor (life cycle) in information attributes and information transmission is also discussed. The results confirm differences in the spread of posts under different topic types, sentiment types, and emotion types on social media. At the same time, the study also found that posts published by users with a high number of followers and users of a media type are more likely to spread on social media. In addition, the study also found that posts with different information attributes are easier to spread on social media during the outbreak and recurrence periods. The driving effect of life cycles is more obvious, especially for topics of prayer and fact, negative sentiment, emotions of fear, and anger. Relevant findings have specific contributions to the information governance of public opinion, the development of social media theory, and the maintenance of network order, which can further weaken the negative impact of information epidemic in the occurrence of public health emergencies, maintain normal social order, and thus create favorable conditions for the further promotion of global recovery.

Analysis of the Evolution of User Emotion and Opinion Leaders’ Information Dissemination Behavior in the Knowledge Q&A Community during COVID-19

Since its emergence in 2019, COVID-19 has quickly triggered widespread public discussion on social media. From 26 February 2020 to 26 September 2020, this study collected data on COVID-19-related posts in the knowledge Q&A community, identified 220 opinion leaders of this community, and used social network analysis and sentiment analysis to analyze the information exchange behavior and emotional evolution of the opinion leaders during COVID-19. The results show that the COVID-19 topic community could be divided into seven main categories. The information dissemination of opinion leader information dissemination network had low efficiency, multiple paths, and a high degree of control. In addition, the emotional evolution of users showed obvious phased characteristics. User emotion changed from initially strong negative to strong positive over the course of the pandemic and eventually tended to be objective and neutral as time passed and the event stabilized.

Social Media Analyst Coverage of Socially Responsible Firms

We examine the influence of corporate social responsibility on the information dissemination behavior of social media analysts (SMAs). We find that SMAs give greater coverage to the earnings announcements of socially responsible firms (SRFs) compared to other firms, particularly for good news announcements. We further investigate whether the difference in coverage for SRFs and non-SRFs is due to superior disclosure practices by SRFs or to positive affective reactions by SMAs. Consistent with an affective response, we find that articles for SRFs appear less tethered to firm fundamentals—the sentiment in SMA articles more poorly predicts future earnings surprises and is less responsive to earnings announcement news for SRFs. Market-based tests similarly suggest that SMA analyses at earnings announcements are of lower quality for SRFs and potentially impair price efficiency. Overall, we attribute our results to SMAs’ desire to view SRFs in a favorable light no matter the disclosure news.

Modeling information dissemination and evolution in time-varying online social network based on thermal diffusion motion

Due to the traditional information dissemination model cannot accurately simulate information dissemination process in the real world, this paper proposes an information diffusion mathematical model and information state node evolution mechanism by using thermodynamic molecular thermal diffusion motion theory, combined with epidemic infection model. Four different network topologies (regular network, small-world network, random network and scale-free network) are applied in the time-varying online social network (OSN) of information dissemination process. Information entropy is also introduced in the information dissemination of OSN. Information is essentially a special form of matter; the propagation process is a process in which the system transitions from one stable state to another. A transfer function is built by some information parameters such as information energy, information temperature, and energy entropy. It reveals the relationship between the state of microscopic network nodes and the macro iterative evolution rules, and carries out simulation experiments and empirical comparative experiments in a variety of networks with different topological structures. The proposed model is trained and evaluating using truth experimental data collected in Baidu network. The experimental results show that the similarity between the simulation results and the real data is greater than 0.96, the correlation is greater than 0.95, and the peak value of the local error is less than 0.2. The mathematical model accurately describes the internal laws and mechanisms of the information dissemination behavior and proves the proposed mathematical propagation model. The transfer function and evolution mechanism are reasonable and effective; the proposed information propagation model not only has strong extensibility, but also provides theoretical support for research in related fields.

Determinants of users’ information dissemination behavior on social networking sites

PurposeAs a new communication paradigm, social networking sites (SNS) have boosted information diffusion and viral marketing. Prior researchers have identified various factors affecting information dissemination on SNS. However, they often focus on limited factors and there is a lack of an integrated theoretical framework that explains aspects of relevant factors. Besides, the research on the impacts of relationships on individual retweeting behavior is still controversial. The purpose of this paper is to propose a theoretical framework to systematically investigate the determinants of individual dissemination behavior on SNS based on the elaboration likelihood model (ELM). Moreover, the authors also examine the relative importance of those relevant factors.Design/methodology/approachThe authors randomly selected 1,250 members of Twitter and crawled posts published by each member since he/she created the Twitter account using Twitter API. The authors processed the data to create panel data and tested hypotheses with the panel logit model.FindingsFactors both on the central route and on the peripheral route of ELM have positive impacts on individual dissemination behavior. Among them, information receiver-related factor and relationships-related factors are the most influential. Contrastingly, source-related factors are the least influential. Furthermore, the authors find that social tie strength mediates almost 50 percent of the effect of value homophily on individual dissemination behavior.Originality/valueThe authors are the first to directly apply ELM to examine individual dissemination behavior on SNS. By integrating factors into the two information processing routes, They incorporate relevant factors into the model and systematically analyze their impacts on individual retweeting behavior on SNS. The research offers at least one explanation for the contradictory findings about the effect of homophily on individual sharing behavior in previous research. The authors propose new variables that gauge topical relevance and interpersonal value homophily on SNS.

Analysis of the key influencing factors of haze information dissemination behavior and motivation in WeChat

PurposeWith the development of mobile internet, instant messaging (IM) applications have gradually changed the way to receive information and communicate with friends. Considered as one of the important social media platforms, WeChat is the most popular IM application in China. This paper aims to examine the influence factors of haze information’s dissemination in WeChat.Design/methodology/approachBased on the theory of information dissemination and the theory of motivation, three information dissemination elements including information source, information and information receiver were proposed in the structural equation model. The model was tested using data collected from both online and offline questionnaire survey results. The data analysis from 170 valid responses confirmed the path effects that emotional motivation, social motivation of information receiver and the credibility of information source positively influenced WeChat users’ re-transmission intention and information emotional tendency negatively influenced their re-transmission intention.FindingsThe research model revealed these key factors that affected dissemination of haze information in WeChat. More importantly, it provided a decision-making framework to release the public emergency information in WeChat. Hence, the paper made an important contribution to practical guidance to relevant decision makers.Originality/valueThis study contributes to the literature on examining factors affecting the haze information transmission in WeChat. A framework was proposed to describe the information dissemination process which comprises information source, information and information receiver.

The Study of Information Dissemination Behavior in Online Social Network with Propagation Delay

In this paper, the information dissemination model involving propagation delay was studied. The effectof delay in the Social Network Service (SNS) was found by considering the theory of complex network and in fectious diseasedynamics. Also, the authors simulate the online social network information dissemination process and classify thedifferent types of nodes. The simulation results show that: as the high connectivity of online social network, there is less threshold of information transmission in network; the propagation delay makes the threshold lower and the information is easier to be spread, but the propagation delay speeds down the information dissemination meanwhile it decreases the possibility of the information out breaking. This study posts a well understanding of the dissemination behavior with propagation delay in the SNS network, which is fundamental research on consensus.

The research of information dissemination model on online social network

In this paper, we propose a general stochastic model for the information dissemination on the online social network. The model considers the node of degree and propagation mechanism, utilizes complex network theory and dynamics of infectious diseases, and finally establishes the dynamic evolution equations. The dynamic evolution equations describe the evolution process of different types of nodes, and show that the propagation process is influenced by network topology and propagation mechanism. We simulate the information spreading process, and analyze the behavior of different types of nodes on online social network. Simulation results show that information can spread easily on the online social network because of the good connectivity. The greater the degree of the initial spread node, the faster the information spreads on online social network. Center nodes have great social influence, and the nodes with different degrees have the similar trend on online social network. Research shows that the model, having the same characteristics with online social network, contributes to a more profound understanding of information dissemination behavior on online social network.

Identification of technological gatekeepers in the information technology profession

Business organizations have become interested in recognizing gatekeepers who may improve business prospects through informal external communication. Past research has identified gatekeepers within organizations, but no technique existed for identifying gatekeepers among groups of people working in an industry, profession, or other external group. This paper develops and tests a simple rule for identifying gatekeepers among members of a profession with a common group of potential interpersonal communication channels. The rule is used to classify gatekeepers among information technology professionals, based on self-reported information dissemination behavior. The rule passes five tests that compare the characteristics and information-seeking strategies of individuals classified using this rule with other members of the profession. The results of the study confirm that self-reported information dissemination behavior can be used to identify gatekeepers among individuals with diverse information-gathering behaviors, but a common group of potential interpersonal communication channels.