Cross-network propagation model of public opinion information and its control in coupled double-layer online social networks

Research on the co-evolution of competitive public opinion and intervention strategy based on Markov process

Under Omni-media environment, Online Social Networks (OSN) have gradually become the most momentous platform for information propagation. Considering the interaction and coexistence of both positive and negative public opinion information (referred to as public opinion), it is of great significance for social development and economic stability to understand the co-evolution process of competitive public opinion and compress the spreading space of negative public opinion. Allowing for this point, this paper constructed a two-stage spreading model of competitive public opinion combing with the actual case of public opinion propagation, analysed the main factors influencing the co-evolution process, such as netizens’ intimacy, network literacy, and so on, and redefined netizens’ state transition probability matrix with the help of Markov process. Then, the effectiveness of the spreading model was verified and the propagation rule of public opinion was discussed in open and closed OSN through simulation experiments. Finally, the intervention strategies were proposed and optimised with the limitation of cost. The results show that the propagation of public opinion mainly depends on netizens’ behaviour with low literacy and presents difference characteristics in two types of OSN. During the intervention process of public opinion propagation, there exists an effective intervention interval and the best intervention strategy varies with the change of network topology. Our research provided a cornerstone for further understanding of the co-evolution process of competitive public opinion and the research conclusions also provided a certain decision-making reference for enterprises, governments and other regulators to reasonably respond to the propagation of public opinion.

Cross-platform opinion dynamics in competitive travel advertising: A coupled networks’ insight

Social media platforms have become an important tool for travel advertisement. This study constructs the bounded confidence model to build an improved cross-platform competitive travel advertising information dissemination model based on open and closed social media platforms. Moreover, this study examines the evolution process of group opinions in cross-platform information dissemination with simulation experiments. Results reveal that based on strong relationships, the closed social media platform opinion leaders better guide in competitive travel advertising and can bring more potential consumers to follow. However, being an opinion leader on an open social media platform will not result in more consumer following.

Research on the co-evolution of temporal networks structure and public opinion propagation

Under the new media environment, social platforms, as the carrier of information propagation, have shown a drastic change in their form and structure, endowing public opinion with unique propagation characteristics. In view of this, considering the dynamic changes of online social network (OSN) structure, this article intends to analyse the spreading mechanism of public opinion in temporal networks and improve the applicability of public opinion governance strategies. Combing the changes of OSN topology with the classical susceptible–infected–recovered (SIR) dynamics model, we constructed a co-evolution model of temporal networks structure and public opinion propagation, and the propagation threshold of public opinion was derived with the help of Markov process. Then, the propagation characteristics of public opinion in temporal networks and their co-evolution process under different factors were discussed through simulation experiments. The results show that the propagation of public opinion in temporal networks has faster speed and wider scope compared with that in static networks; netizens’ social activity has a phased impact on the evolution process of public opinion and with its significant heterogeneity, the propagation of public opinion is gradually suppressed; compared with [Formula: see text], the evolution process of public opinion in temporal networks is more sensitive to the state change of public opinion [Formula: see text]. Our research can further enrich the theoretical research system of network science and information science and also provide a certain decision-making reference for the regulators to reasonably govern the propagation of public opinion in social platforms.

Analysis of the structure and time-series evolution of knowledge label network from a complex perspective

Purpose

The research on social media-based academic communication has made great progress with the development of the mobile Internet era, and while a large number of research results have emerged, clarifying the topology of the knowledge label network (KLN) in this field and showing the development of its knowledge labels and related concepts is one of the issues that must be faced. This study aims to discuss the aforementioned issue.

Design/methodology/approach

From a bibliometric perspective, 5,217 research papers in this field from CNKI from 2011 to 2021 are selected, and the title and abstract of each paper are subjected to subword processing and topic model analysis, and the extended labels are obtained by taking the merged set with the original keywords, so as to construct a conceptually expanded KLN. At the same time, appropriate time window slicing is performed to observe the temporal evolution of the network topology. Specifically, the basic network topological parameters and the complex modal structure are analyzed empirically to explore the evolution pattern and inner mechanism of the KLN in this domain. In addition, the ARIMA time series prediction model is used to further predict and compare the changing trend of network structure among different disciplines, so as to compare the differences among different disciplines.

Findings

The results show that the degree sequence distribution of the KLN is power-law distributed during the growth process, and it performs better in the mature stage of network development, and the network shows more stable scale-free characteristics. At the same time, the network has the characteristics of “short path and high clustering” throughout the time series, which is a typical small-world network. The KLN consists of a small number of hub nodes occupying the core position of the network, while a large number of label nodes are distributed at the periphery of the network and formed around these hub nodes, and its knowledge expansion pattern has a certain retrospective nature. More knowledge label nodes expand from the center to the periphery and have a gradual and stable trend. In addition, there are certain differences between different disciplines, and the research direction or topic of library and information science (LIS) is more refined and deeper than that of journalism and media and computer science. The LIS discipline has shown better development momentum in this field.

Originality/value

KLN is constructed by using extended labels and empirically analyzed by using network frontier conceptual motifs, which reflects the innovation of the study to a certain extent. In future research, the influence of larger-scale network motifs on the structural features and evolutionary mechanisms of KLNs will be further explored.

Research on the propagation and governance of public opinion information under the joint action of internal and external factors

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Practical implications

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.

Originality/value

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.