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In social media, crisis information susceptible of generating different emotions could be spread at exponential pace via multilevel super-spreaders. This study aims to interpret the multi-level emotion propagation in natural disaster events by analyzing information diffusion capacity and emotional guiding ability of super-spreaders in different levels of hierarchy.

We collected 47,042 original microblogs and 120,697 forwarding data on Weibo about the “7.20 Henan Rainstorm” event for empirical analysis. Emotion analysis and emotion network analysis were used to screen emotional information and identify super-spreaders. The number of followers is considered as the basis for classifying super-spreaders into five levels.

Official media and ordinary users can become the super-spreaders with different advantages, creating a new emotion propagation environment. The number of followers becomes a valid basis for classifying the hierarchy levels of super-spreaders. The higher the level of users, the easier they are to become super-spreaders. And there is a strong correlation between the hierarchy level of super-spreaders and their role in emotion propagation.

This study has important significance for understanding the mode of social emotion propagation and making decisions in maintaining social harmony.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-03-2024-0192.

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.

The pandemic has enhanced the global phenomenon of disinformation. This paper aims to study the false news concerning COVID-19, spread through social media in Spain, by using the LatamChequea database for a duration from 01/22/2020, when the first false information has been detected, up to 03/09/2021.

A quantitative analysis has been conducted with regard to the correlation between fake news stories and the pandemic state, the motive to share them, their dissemination in other countries and the effectiveness of fact checking. This study is complemented by a qualitative method: a focus group conducted with representatives of different groups within the society.

Fake news has been primarily disseminated through several social networks at the same time, with two peaks taking place in over a half of the said false stories. The first took place from March to April of 2020 during complete lockdown, and we were informed of prevention measures, the country’s situation and the origin of the virus, whereas the second was related to news revolving around the coming vaccines, which occurred between October and November. The audience tends to neither cross-check the information received nor report fake news to competent authorities, and fact-checking methods fail to stop their spread. Further awareness and digital literacy campaigns are thus required in addition to more involvement from governments and technological platforms.

The main limitation of the research is the fact that it was only possible to conduct a focus group of five individuals who do not belong to generation Z due to the restrictions imposed by the pandemic, although a clear contribution to the analysis of the impact of fake news on social networks during the COVID-19 pandemic in Spain can be seen from the privileged experiences in each of the fields of work that were identified. In this sense, the results of the study are not generalizable to a larger population. On the other hand, and with a view to future research, it would be advisable to carry out a more specific study of how fake news affects generation Z.

This research is original in nature, and the findings of this study are valuable for business practitioners and scholars, brand marketers, social media platform owners, opinion leaders and policymakers.

This study aims to use geographical information on social media for public opinion risk identification during a crisis.

This study constructs a double-layer network that associates the online public opinion with geographical information. In the double-layer network, Gaussian process regression is used to train the prediction model for geographical locations. Second, cross-space information flow is described using local government data availability and regional internet development indicators. Finally, the structural characteristics and information flow of the double-layer network are explored to capture public opinion risks in a fine-grained manner. This study used the early stages of the COVID-19 outbreak for validation analyses, and it collected more than 90,000 pieces of public opinion data from microblogs.

In the early stages of the COVID-19 outbreak, the double-layer network exhibited a radiating state, and the information dissemination was more dependent on the nodes with higher in-degree. Moreover, the double-layer network structure showed geographical differences. The risk contagion was more significant in areas where information flow was prominent, but the influence of nodes was reduced.

Public opinion risk identification that incorporates geographical scenarios contributes to enhanced situational awareness. This study not only effectively extends geographical information on social media, but also provides valuable insights for accurately responding to public opinion.

Despite the continued focus on online sharing through social media, little consumer research has looked at this behavior as an independent construct or tried to determine how it relates to other consumer behaviors. Consequently, this study aims to explore the concept of social media sharing disposition (SMSD), proposes a measure of the construct, and, in five studies, assesses its reliability and validity and its relationship to other online and offline consumer behaviors.

Five studies using surveys were carried out to assess the SMSD construct. The studies gathered data to assess the properties and validities of SMSD, as well as its ability to assess offline and online sharing behavior.

The results indicate that SMSD is a useful construct that helps to explain people’s social media and offline sharing behavior, although its focus is primarily on social media sharing. It also displays convergent, discriminant and predictive validity. These results indicate that SMSD can be used to predict the likelihood of consumers sharing online information. They also confirm that SMSD works effectively in different cultural contexts. SMSD can also be used to assess consumer offline sharing behavior.

There was neither an investigation of actual differences in behaviors among consumers in the number of posts or online reviews they undertook, based on SMSD, nor a study of whether individuals are more likely to incorporate brand information into their posts. Future research could explore these behaviors to determine whether they can be explained by SMSD. There was also no focus on a rationale for engaging in social media sharing; that is, there are no proposed antecedents of SMSD. Additional studies could assess antecedents of this construct.

Marketers interested in engaging consumers as participants in the dissemination of online (electronic) information can segment and target consumers on the basis of SMSD. Therefore, it can be used to determine who should be targeted with information to disperse to other consumers. It is likely that there is a relationship between SMSD and social media influencer (SMI) activity, so it could also be used to identify SMIs among consumer bases. It can also be adapted and applied to understanding offline sharing behavior.

The paper reports on SMSD and establishes that it is an additional construct that can help explain consumer information sharing. The construct relates to a social media context, where it may be increasingly difficult to identify consumers who engage in differential sharing of digital information.

This study aims to investigate the current practices being implemented against the dissemination of fake online news, identify the relationship of new media literacy (NML) with fake news epidemic control and find out the challenges in identifying valid sources of information.

To accomplish constructed objectives of this study, a systematic literature review (SLR) was conducted. The authors carried out the “Preferred Reporting Items for the Systematic Review and Meta-analysis” guidelines as a research methodology. The data were retrieved from ten world’s leading digital databases and online tools. A total of 25 key studies published in impact factor (IF) journals were included for systematic review vis-à-vis standard approaches.

This study revealed trending practices to control fake news consisted of critical information literacy, civic education, new thinking patterns, fact-checkers, automatic fake news detection tools, employment of ethical norms and deep learning via neural networks. Results of the synthesized studies revealed that media literacy, web literacy, digital literation, social media literacy skills and NML assisted acted as frontline soldiers in combating the fake news war. The findings of this research also exhibited different challenges to control fake news perils.

This study provides pertinent theoretical contributions in the body of existing knowledge through the addition of valuable literature by conducting in-depth systematic review of 25 IF articles on a need-based topic.

This scholarly contribution is fruitful and practically productive for the policymakers belonging to different spectrums to effectively control web-based fake news epidemic.

This intellectual piece is a benchmark to address fake news calamities to save the social system and to educate citizens from harms of false online stories on social networking websites.

This study vivifies new vistas via a reinvigorated outlook to address fake news perils embedded in dynamic, rigorous and heuristic strategies for redefining a predetermined set of social values.

As one of China’s most influential social platforms, Xiaohongshu is considered an underexploited market with significant user traffic. This study aims to build on existing scholarly work on social media marketing by conducting an empirical analysis of Xiaohongshu’s content to explore effective marketing strategies for children’s books.

This study uses qualitative content analysis to investigate the marketing practices for children’s books on Xiaohongshu. By systematically coding and interpreting data, the authors identified core marketing strategies and their interactions among publishers of children’s books on the platform.

Based on viral marketing and social proof theories, the analysis delineates practices and interrelations among three key marketing strategy components: content creation, traffic navigation and sales conversion on Xiaohongshu. From this analysis, a conceptual model titled “Continuous ‘Planting a Seed’ of Interest: Strategies for Marketing Children’s Books on Xiaohongshu” was developed.

This research not only corroborates the existing literature on the transformative power of social media in marketing but also extends it by providing a focused examination of how these principles apply to the promotion of children’s books on Xiaohongshu. It also provides practical insights for publishers looking to develop effective marketing strategies.

This study employs bibliometric analysis to map the research landscape of social media trending topics during the COVID-19 pandemic. The authors aim to offer a comprehensive review of the predominant research organisations and countries, key themes and favoured research methodologies pertinent to this subject.

The authors extracted data on social media trending topics from the Web of Science Core Collection database, spanning from 2009 to 2022. A total of 1,504 publications were subjected to bibliometric analysis, utilising the VOSviewer tool. The study analytical process encompassed co-occurrence, co-authorship, citation analysis, field mapping, bibliographic coupling and co-citation analysis.

Interest in social media research, particularly on trending topics during the COVID-19 pandemic, remains high despite signs of the pandemic stabilising globally. The study predominantly addresses misinformation and public health communication, with notable focus on interactions between governments and the public. Recent studies have concentrated on analysing Twitter user data through text mining, sentiment analysis and topic modelling. The authors also identify key leading organisations, countries and journals that are central to this research area.

Diverging from the narrow focus of previous literature reviews on social media, which are often confined to particular fields or sectors, this study offers a broad view of social media's role, emphasising trending topics. The authors demonstrate a significant link between social media trends and public events, such as the COVID-19 pandemic. The paper discusses research priorities that emerged during the pandemic and outlines potential methodologies for future studies, advocating for a greater emphasis on qualitative approaches.

The peer-review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2023-0194.

This research exclusively focuses on China’s elderly Internet users given how severe a threat disinformation has become for this particular population group as social media platforms thrive and the number of elderly netizens grows in China. The purpose of this study is to explore the mechanism of how elderly social media users’ intention to identify false information is influenced helps supplement the knowledge system of false information governance and provides a basis for correction practices.

This study focuses on the digital literacy of elderly social media users and builds a theoretical model of their intention to identify false information based on the theory of planned behaviour. It introduces two variables – namely, risk perception and self-efficacy – and clarifies the relationships between the variables. Questionnaires were distributed both online and offline, with a total of 468 collected. A structural equation model was built for empirical analysis.

The results show that digital literacy positively influences risk perception, self-efficacy, subjective norms and perceived behavioural control. Risk perception positively influences subjective norms, perceived behavioural control and the attitude towards the identification of false information. Self-efficacy positively influences perceived behavioural control but does not significantly impact the intention to identify. Subjective norms positively influence the attitude towards identification and the intention to identify. Perceived behavioural control positively influences the attitude towards identification but does not significantly impact the intention to identify. The attitude towards identification positively influences the intention to identify.

Based on relevant theories and the results of the empirical analysis, this study provides suggestions for false information governance from the perspectives of social media platform collaboration and elderly social media users.

This study aimed to examine the research hotspots and evolution paths in the field of health information behavior (HIB) in China and abroad, and conduct comparative analysis to better understand its development trajectory globally.

A keyword search of the relevant literature included in the China National Knowledge Infrastructure (CNKI) database and Web of Science (WoS) core collection database was conducted, using the visualized analysis tool CiteSpace V for bibliometric analyses.

The common research hotspots in China and abroad can be divided into related research on HIB, research on its influencing factors and health information research. Among these, health information-seeking behavior has been the focus of domestic and foreign scholars. From the subdivision perspective, the focus of Chinese and foreign research hotspots differs. In terms of evolutionary path, the initial stage of HIB research in China and abroad revolves around health information and health information-seeking behavior, followed by the influencing factors of HIB; however, the research breakthrough point is the reverse. Then, domestic and foreign research was conducted on different types of HIBs. Regarding the selection of research objects, Chinese and foreign research objects were increasingly diversified.

This study also has several limitations. First, the literature sample only selected the literature in the WoS and CNKI databases, and there may be many HIB-related works published in other databases. Therefore, future research should include other databases. Second, in terms of language, this study selected only Chinese and English literature, but in many countries, important research results on certain topics are usually published in native language, and future research should expand the language selection. Third, this study only conducted national and institutional collaboration network analysis, keyword co-occurrence analysis, cluster analysis and timeline chart analysis.

The implication of practice can be divided into the following three points. (1) Analyzing the domestic and foreign literature on HIB and identifying highly cooperative institutions and countries in the field of HIB can reveal the research situation of HIB and help researchers establish new research networks in the future. (2) Analyzing the research hotspots and evolutionary paths of HIB at home and abroad is helpful for quickly understanding the development context of this field and grasping the emerging research directions such as HIB of people in close contact with patients, health information exchange behavior, health information avoidance behavior and health information discontinuation behavior, which can help researchers to explore the future research direction in this field, so as to determine the topic and fill the research gap. (3) Combining the analysis of HIB-related research at home and abroad is helpful for professionals to understand the characteristics and rules of HIB of users, consumers and other groups to further optimize and improve health information services.

Comparing and summarizing the research status of HIB in China and globally, and presenting the findings visually, will help researchers better grasp the research overview and hotspot changes in this field, as well as provide a follow-up reference.