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Under the background of coexistence of information overload and information fragmentation, it is of great significance to identify influencing factors and reveal the evolution logic of public opinion for public opinion governance.

Taking 24 hot social events as research cases, firstly, the evolution process of public opinion was divided into initial stage and response stage. Secondly, eight antecedent variables were extracted for qualitative comparative analysis of fuzzy sets. Finally, the configuration path of public opinion evolution results was summarized.

The research showed that compared with the initial stage, the influencing factors in the reaction stage played a key role in the continuous evolution of public opinion. The influencing factors in the initial stage and response stage played an indispensable role in promoting the evolution of public opinion to calm down.

This research can provide reference for regulators to timely grasp the initiative, discourse power and leadership of public opinion development.

Research on the two-stage configuration path of public opinion evolution is helpful to clarify the key factors affecting the evolution trend of online public opinion of hot events.

Various decision opinions comprise the foundation of emergency decision-making. However, decision-makers have difficulty establishing trust relationships within a short time because of decision-making groups being temporary. The paper aims to develop an ambiguity-incorporated opinion formation model that considers ambiguous opinions on relevant risks from a psychological perspective during the consensus reaching process.

Addressing the problem of forming a consensus decision-making opinion in an ambiguous environment and relevant risk opinions, different social network structures were first proposed. Subsequently, psychological factors affecting the decision-makers' perception of ambiguous opinions and tolerance for ambiguity under the multi-risk factors were considered. Accordingly, an ambiguity-incorporated opinion formation model was proposed by considering the ambiguity and relevant opinions on multi-risk factors.

A comparison between the ambiguity-incorporated opinion formation model and the F–J model illustrates the superiority of the proposed model. By applying the two types of network structures in the simulation process, the results indicate that the convergence of opinions will be affected by different decision-making network structures.

The research provides a novel opinion formation model incorporating psychological factors and relevant opinions in the emergency decision-making process and provides decision support for practitioners to quantify the influence of ambiguous opinions. The research allows the practitioners to be aware of the influence of different social network structures on opinion formation and avoid inaccurate opinion formation due to unreasonable grouping in emergency decision-making.

Under the new media environment, while enjoying the convenience brought by the propagation of public opinion information (referred to as public opinion), learning the evolution process of public opinion and strengthening the governance of the spreading of public opinion are of great significance to promoting economic development and maintaining social stability as well as effectively resisting the negative impact of its propagation.

Thinking about the results of empirical research and bibliometric analysis, this paper focused on introducing key factors such as information content, social strengthening effects, etc., from both internal and external levels, dynamically designed public opinion spreading rules and netizens' state transition probability. Subsequently, simulation experiments were conducted to discuss the spreading law of public opinion in two types of online social networks and to identify the key factors which influencing its evolution process. Based on the experimental results, the governance strategies for the propagation of negative public opinion were proposed finally.

The results show that compared with other factors, the propagation of public opinion depends more on the attributes of the information content itself. For the propagation of negative public opinion, on the one hand, the regulators should adopt flexible guidance strategy to establish a public opinion supervision mechanism and autonomous system with universal participation. On the other hand, they still need to adopt rigid governance strategy, focusing on the governance timing and netizens with higher network status to forestall the wide-diffusion of public opinion.

The research conclusions put forward the enlightenment for the governance of public opinion in management practice, and also provided decision-making reference for the regulators to reasonably respond to the propagation of public opinion.

Our research proposed a research framework for the discussion of public opinion propagation process and had important practical guiding significance for the governance of public opinion propagation.

The purposes of the study were to classify South Korean female apparel shoppers into fashion opinion leadership groups and to develop group profdes by lifestyle characteristics, store selection attributes, clothing purchase influences, and sociodemographics. Data (N=271) were collected by questionnaires distributed to 300 South Korean consumers chosen to participate in the investigation. By cluster analysis of the Fashion Opinion Leadership (FOL) scale, four female consumer groups were identified as traditionoriented/culture conscious (29.4 per cent), eco‐nomic‐oriented/price conscious (15.8 per cent), convenience‐oriented/time conscious (28.7 per cent), and appearance‐oriented/fashion conscious (26.1 per cent). Scale reliability with the inter‐national sample was determined by a Cronbach alpha. Groups were compared on the profile descriptors through MANOVA and chisquare statistics. Results indicated that fashion opinion leadership is a base for segmenting South Korean female apparel shoppers. This study suggests ways knowledge about the consumer groups identified can be incorporated into marketing and retail strategies.

This paper aims to examine innovativeness and extraversion as antecedents of perceived and social media opinion leadership in different country-level contexts and explore how these antecedents influence product adoption differently.

A survey method was used to collect data from Turkey and the USA. A total of 415 respondents participated in two studies, and data were analyzed using structural equation modeling.

This research shows that innovativeness affects perceived opinion leadership, whereas extraversion affects social media opinion leadership, and these effects are moderated by country-level differences.

Tthis research provides strategic information strategic information on how to identify and target influencers in social media across countries. This paper has implications for marketers who are trying to find influential consumers to increase new product adoption. Social media opinion leaders are important seeding points, because they actively initiate new product adoption for other consumers. Marketers should create strategies that are in line with the country’s cultural orientation in addition to personal/psychological traits.

This research provides valuable information to better explain the consumers’ adoption of technological products and the factors affecting this process in the context of social media. Specifically, this paper identifies strategies to use cultural differences across countries (i.e. Turkey versus the USA) and personality traits (i.e., innovativeness and extraversion) in the adoption of new products.

This paper extends prior literature on opinion leadership by uncovering consumer dynamics internationally, which are known to influence social media use. Specifically, by examining the effect of innovativeness and extraversion on opinion leadership in different countries, this research contributes to the literature on new product adoption and has implications for effectively identifying influencers in social media.

Examines the characteristics of young innovators (i.e. those in a group who accept the innovation first, for instance a hula hoop, a mobile phone or a video game) and opinion leaders (i.e. the person in a group who tends to be copied or consulted for advice); the two roles overlap, as child innovators are usually also opinion leaders, but not necessarily the reverse. Explains the Diffusion of Innovations theory, relating it to the adoption by children of new products and behaviours, i.e. their socialisation as consumers; this process involves the stages of awareness, interest, evaluation, test purchase, and adoption. Outlines the characters involved in the generalised theory of Diffusion of Innovations: opinion leaders, innovators, gatekeepers (for instance parents who allow their children to acquire a new product), and change agents (an outsider who gives advice, for instance a teacher). Discusses whether there are generalised innovators and opinion leaders, i.e. whether the same people tend to fulfil these roles in all or most areas. Moves onto a 2003 study of children which surveyed how well the Diffusion of Innovations theory fits them, how much overlap there was among innovators and opinion leaders, and where children got information about new products. Concludes that the Diffusion of Innovations theory does roughly fit child and teenage behaviour; in the adoption process, personal communication plays a dominant role, followed by television and advertising, but mobile phone and SMS messages played almost no role among eight to 12‐year‐olds in communicating information on new products.

The importance of retail store attributes for apparel shopping was examined for elderly (65 and over) men and women (65 and older). A self‐administered mail‐in survey questionnaire was used to collect data for the study. The data were analysed using descriptive statistics, factor analysis, and one‐way analysis of variance (ANOVA). Cronbach's alpha was executed to determine the reliability of the extracted factors. Four extracted factors explained 67.76 per cent of the total variance with regard to the preferences for the retail store attributes by the participating older men and women. Sex was identified as the most discriminating variable for both the extracted factors and fashion opinion leadership variables. Implications of the results for future research in both the US and international settings are discussed.

The purpose of this paper is to develop a multi-agent-based simulation model for the online opinion dissemination during hazardous chemical leakage emergencies into rivers in China, to explore an appropriate crisis information release policy of China’s government for controlling public panic.

In the proposed model, two fundamental attributes of crisis information, i.e., truthfulness (for true or false news) and attitude (for positive, neutral or negative opinion), are considered. Four major agents in the online community system, i.e., citizens, the government, media and opinion leaders, are included. Using four typical accidents of hazardous chemical leakage into rivers in China as case studies, insightful policy implications can be obtained for crisis management and panic control.

The news about the terrible potential damages from such a type of accidents will instantly arise wide-ranging public panic; therefore, the corresponding crisis information release policy should be carefully designed. It is strongly advised against publishing false news to temporarily conceal the accidents, which will seriously hurt the government’s reputation and agitate much larger-scale public panic in terms of degree and duration. To mitigate public panic, the true news especially about treatment measurements should be published immediately. If the government does nothing and releases no crisis information, the public panic will go out of control.

This paper only focuses on the crisis information release policies from the perspectives of the government. Furthermore, this study especially focuses on the cases in China, and extending the proposed model study for general contexts is an important direction to improve this study. Finally, the proposed model should be extended to other types of emergencies to further justify its generalization and universality, especially various natural catastrophes like storms, floods, tsunamis, etc.

This paper develops a multi-agent-based model for online public opinion dissemination in emergency to explore an appropriate crisis information release policy for controlling public panic stemming from hazardous chemicals leakage accidents into rivers. The proposed model makes major contributions to the literature from two perspectives. First, the crisis information about emergency accidents are divided into true and false news based on the truthfulness attribute, and into neutral, positive and negative emotions based on the attitude attribute. Second, the proposed model covers the main agents in the online virtual community.

This study aims to propose a method known as the fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) for complex project selection in organizations. To fulfill study objectives, the factors responsible for making a project complex are collected through literature review, which is then analyzed by fuzzy TOPSIS, based on three decision-makers’ opinions.

The selection of complex projects is a multi-criteria decision-making (MCDM) process for global organizations. Traditional procedures for selecting complex projects are not adequate due to the limitations of linguistic assessment. To crossover such limitation, this study proposes the fuzzy MCDM method to select complex projects in organizations.

A large-scale engine manufacturing company, engaged in the energy business, is studied to validate the suitability of the fuzzy TOPSIS method and rank eight projects of the case company based on project complexity. Out of these eight projects, the closeness coefficient of the most complex project is found to be 0.817 and that of the least complex project is found to be 0.274. Finally, study outcomes are concluded in the conclusion section, along with study limitations and future works.

The outcomes from this research may not be generalized sufficiently due to the subjectivity of the interviewers. The study outcomes support project managers to optimize their project selection processes, especially to select complex projects. The presented methodology can be used extensively used by the project planners/managers to find the driving factors related to project complexity.

The presented study deliberately explained how complex projects in an organization could be select efficiently. This selection methodology supports top management to maintain their proposed projects with optimum resource allocations and maximum productivity.

A novel asynchronous network-based model is proposed in this paper for the sentiment analysis of online public opinions. This new model provides a new approach to analyze the evolution characteristics of online public opinion sentiments in complex environment.

Firstly, a new sentiment analysis model is proposed based on the asynchronous network theory. Then the graphical evaluation and review technique is employed and extended to design the model-based sentiment analysis algorithms. Finally, simulations and real-world case studies are given to show the effectiveness of the proposed model.

The dynamics of online public opinion sentiments are determined by both personal preferences to certain topics and the complex interactive influences of environmental factors. The application of appropriate quantitative models can improve the prediction of public opinion sentiment.

The proposed model-based algorithms provide simple but effective ways to explore the complex dynamics of online public opinions. Case studies highlight the role of government agencies in shaping sentiments of public opinions on social topics.

This paper proposes a new asynchronous network model for the dynamic sentiment analysis of online public opinions. It extends the previous static models and provides a new way to extract opinion evolution patterns in complex environment. Applications of the proposed model provide some new insights into the online public opinion management.