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As 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.

The 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.

Factors 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.

The 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.

This study aims to explore the influencing factors on college students’ behaviours of spreading Internet public opinion on emergencies in colleges and universities. This study provides a reference for these institutions to cope with and reduce the influence of Internet public opinion on emergencies and maintain their normal teaching order.

In this study, a research model by using motivation theory and design a questionnaire on the basis of relevant literature are constructed. This paper surveys college students and collects a total of 317 valid questionnaires. On the basis of the reliability and validity of the questionnaire, this study verifies the proposed model by using Smart PLS.

The results show that social motivation and information source preference have significant positive influences on college students’ willingness to spread Internet public opinion on emergencies in colleges and universities. Moreover, information source preference has a significant moderating effect on the relationship between social motivation and dissemination willingness. If college students’ information source preference is high, then the moderating effect is significant. The extent of college students’ interaction and involvement has a significantly positive influence on their trust in the dissemination platform for Internet public opinion on emergencies in colleges and universities. Egoism has a significantly positive influence on the social motivation of college students to spread Internet public opinion on emergencies in colleges and universities. Involvement degree has a significant moderating effect on the relationship between social motivation and trust. If college students’ involvement degree is low, then the moderating effect is significant. Thus, when the involvement of college students in Internet public opinion on emergencies in colleges and universities is low, the influence of social motivation on trust is great.

This study increases the influencing factors in the literature on Internet public opinion, enriches the research theory of Internet public opinion on emergencies in colleges and universities and expands the application scope of the theory of social motivation. The conclusion provides guidance for colleges and students to govern Internet public opinion on emergencies and improve the ability of these institutions in dealing with Internet public opinion on emergencies.

The online Question and Answer community is full of a large number of science and technology topics, the discussion and dissemination of which play an important role in promoting the popularization of new technologies and cultivating public enthusiasm for science. However, the spread of false information and rumors weakens the community's positive effect, making the community more difficult for people to obtain useful information on such topics. Research on the influencing factors and governance of the spread of false information on science and technology topics has become the key to the spread of popular science.

Therefore, this paper uses the Elaboration Likelihood Model as the theoretical framework to examine the role of the factors influencing the spread of false information on science and technology topics in Zhihu community on the information persuasion and the impact on public behavior attitude from the core path and the edge path. This paper compiles a crawler program to capture 12,893 response information under the “Metaverse” topic in Zhihu community as an empirical sample and uses text mining and conducts visual correlation analysis to explore the key factors affecting the persuasive transmission path of information on science and technology topics.

The research finds that the content specialization, content consistency and content coherence of science and technology topics affect personal judgment from the aspect of information content through the core path and have a positive correlation with information persuasion; the number of comments, the length of the text and the publishing authors' influence from the edge image characteristics through the edge path are positively correlated with the information persuasion. Then, from the perspective of topic platform, government and topic participants, this paper puts forward a general plan to improve the information persuasion of science and technology topics so as to deal with false information.

Compared with the small data set of the traditional questionnaire survey, the research based on community empirical big data is more reliable. The model takes into account the attitude and behavior of users and is more suitable for the research on the transmission path of scientific and technological information in the internet era. This research provides a direction for analyzing the text characteristics and development trends of information in the field of science and technology and is conducive to promoting the optimization of the network information environment and building a good ecology, with the spread of rumors about science and technology topics curbed and the governance of false information strengthened.

Retail investors are prone to be affected by information dissemination in social media with the rapid development of Web 2.0. The purpose of this study is to recognize the factors that may impact users' retweet behavior, namely information dissemination in the online financial community, through machine learning techniques.

This paper crawled data from the Chinese online financial community (Xueqiu.com) and extracted author-related, content-related, situation-related, stock-related and stock market-related features from the dataset. The best information dissemination prediction model based on these features was determined by evaluating five classifiers with various performance metrics, and the predictability of different feature groups was tested.

Five prevalent classifiers were evaluated with various performance metrics and the random forest classifier was proven to be the best retweet prediction model in the authors’ experiments. Moreover, the predictability of author-related, content-related and market-related features was illustrated to be relatively better than that of the other two feature groups. Several particularly important features, such as the author's followers and the rise and fall of the stock index, were recognized in this paper at last.

This study contributes to in-depth research on information dissemination in the financial domain. The findings of this study have important practical implications for government regulators to supervise public opinion in the financial market.

With 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.

Based 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.

The 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.

This 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.

Alliances have been increasing at an alarming rate for the past decade. Many of these alliances are used predominately in the supply chain side of businesses and industries. They are used to facilitate communication and interaction between firms that require resources of one another. Alliances facilitate the learning that takes place between firms involved in them. The aim of this article is to take an alliance learning perspective in explaining the processes of information dissemination and communication between firms involved in supply chain management. A conceptual model is developed which examines the learning and information communication dynamics of supply chain management in an alliance setting. Propositions are espoused which led to future research directions being discussed.

The purpose of this paper is to provide a critical discussion of the paucity of research on information behaviour of information providers and to propose a framework for investigating the emerging area of provider information behaviour.

The approach takes the form of a conceptual analysis and literature review.

A multidisciplinary framework is provided to form the basis of further exploration of provider information behaviour.

There are various types of information providers and they provide opportunities for exploring and comparing their range of information activities and developing models of provider information behaviour.

The paper argues for a new perspective to the study of information behaviour. The paucity of research on internal users of information has not matched those on external users of information over the years. An exploration of provider information behaviour together with its internal impact can provide insights which will help organisations better understand best practice, predict effects of new behaviours during periods of change and make informed decisions. It will also aid in the development of the teaching of information and library skills.

This study aims to improve disaster management. Social media, particularly microblog, has become a new platform for public opinion dissemination. However, few studies have been conducted to explore the structure of public opinions, the approaches for facilitating the spread of public opinions and the results of public opinion dissemination in the context of mobile internet for the purpose of improving disaster management.

This paper chooses Ebola as the research topic and extracts 14,735 Ebola-related data items from Sina Microblogs to examine the information nodes of public opinion and the characteristics of propagation paths on mobile internet. Particularly, nodes of public opinion between mobile terminals and non-mobile terminals are compared.

The results of this paper reveal the characteristics of public opinion propagation on mobile internet and verify the effectiveness of public opinion propagation on mobile internet. This study shows that public opinions propagate quickly, widely and efficiently and further generate great impacts on mobile internet.

The methods used in this study can be useful for the government agencies and other relevant organizations to monitor public opinions, identify issues and problems proactively and develop strategies in a more efficient manner to improve disaster management.

The results of this paper are helpful for related departments to monitor public opinions and to further improve disaster management.

This paper explores the mechanism of public opinion dissemination on mobile internet and further investigates how to improve disaster management through a case study related to Ebola.

The impact of COVID-19 has led to a surge in the public’s reliance on the Internet for pandemic information, and the policy of home isolation has exacerbated this. This study aimed to investigate public information needs and ways of accessing and disseminating information during COVID-19 in mainland China.

This study used a qualitative research approach to conduct semi-structured interviews with 15 participants from 9 cities in mainland China about information needs and access behaviors during the COVID-19 outbreak. All interview recordings were converted into text and proofread, then coded and summarised in correspondence with the research questions using the grounded theory.

This study summarized the dynamics of public information needs during the 2.5-year pandemic and identified the difficulties in accessing certain information.

Although information needs of public health emergencies have been a hot topic during COVID-19, scant studies focus on information needs in specific countries in Asia, especially in mainland China, the first country with a major outbreak and stringent lockdown mandates. Therefore, the current study is well enriched by focusing on information demand behavior in the context of COVID-19. Possible measures for improvement were also given to existing and potential problems, taking into account the participants’ views.

Users' voluntary forwarding behavior opens a new avenue for companies to promote their brands and products on social networking sites (SNS). However, research on voluntary information disseminators is limited. This paper aims to bring an in-depth understanding of voluntary disseminators by answering the following questions: (1) What is the underlying mechanism by which some users are more enthusiastic to voluntarily forward content of interest? (2) How to identify them? We propose a theoretical model based on the Elaboration-Likelihood Model (ELM) and examine three types of factors that moderate the effect of preference matching on individual forwarding behavior, including personal characteristics, tweet characteristics and sender–receiver relationships.

Via Twitter API, we randomly crawled 1967 Twitter users' data to validate the conceptual framework. Each user’s original tweets and retweeted tweets, profile data such as the number of followers and followees and verification status were obtained. The final corpus contains 163,554 data points composed of 1,634 valid twitterers' retweeting behavior. Tweets produced by these core users' followees were also crawled. These data points constitute an unbalanced panel data and we employ different models — fixed-effects, random-effects and pooled logit models — to test the moderation effects. The robustness test shows consistency among these different models.

Preference matching significantly affects users' forwarding behavior, implying that SNS users are more likely to share contents that align with their preferences. In addition, we find that popular users with lots of followers, heavy SNS users who author tweets or forward other-sourced tweets more frequently and users who tend to produce longer original contents are more enthusiastic to disseminate contents of interest. Furthermore, interaction strength has a positive moderating effect on the relationship between preference matching and individuals' forwarding decisions, suggesting that users are more likely to disseminate content of interest when it comes from strong ties. However, the moderating effect of perceived affinity is significantly negative, indicating that an online community of individuals with many common friends is not an ideal place to engage individuals in sharing information.

This work brings about a deep understanding of users' voluntary forwarding behavior of content of interest. To the best of our knowledge, the current study is the first to examine (1) the underlying mechanism by which some users are more likely to voluntarily forward content of interest; and (2) how to identify these potential voluntary disseminators. By extending the ELM, we examine the moderating effect of tweet characteristics, sender–receiver relationships as well as personal characteristics. Our research findings provide practical guidelines for enterprises and government institutions to choose voluntary endorsers when trying to engage individuals in information dissemination on SNS.