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1 – 10 of over 68000Lu (Monroe) Meng, Tongmao Li, Xin Huang and Shaobo (Kevin) Li
This paper aims to investigate the impacts of rumors' information characteristics on people's believing and spreading of rumors online.
Abstract
Purpose
This paper aims to investigate the impacts of rumors' information characteristics on people's believing and spreading of rumors online.
Design/methodology/approach
This study employed a mixed-methods approach by combining qualitative and quantitative methods. In study 1, the authors explored different types of rumors and their information source characteristics through qualitative research. In study 2, the authors utilized the findings from study 1 to develop an empirical model to verify the impact of these characteristics on the public's behaviors of believing and spreading rumors by content analysis and quantitative research.
Findings
The results show that five information source characteristics – credibility, professionalism, attractiveness, mystery and concreteness – influence the spreading effect of different types of rumors.
Research limitations/implications
This study contributes to rumor spreading research by deepening the theory of information source characteristics and adding to the emerging literature on the COVID-19 pandemic.
Practical implications
Insights from this research offer important practical implications for policymakers and online-platform operators by highlighting how to suppress the spread of rumors, particularly those associated with COVID-19.
Originality/value
This research introduces the theory of information source characteristics into the field of rumor spreading and adopts a mixed-methods approach, taking COVID-19 rumors as a typical case, which provides a unique perspective for a deeper understanding of rumor spreading's antecedences.
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Mai Miyabe, Akiyo Nadamoto and Eiji Aramaki
– This aim of this paper is to elucidate rumor propagation on microblogs and to assess a system for collecting rumor information to prevent rumor-spreading.
Abstract
Purpose
This aim of this paper is to elucidate rumor propagation on microblogs and to assess a system for collecting rumor information to prevent rumor-spreading.
Design/methodology/approach
We present a case study of how rumors spread on Twitter during a recent disaster situation, the Great East Japan earthquake of March 11, 2011, based on comparison to a normal situation. We specifically examine rumor disaffirmation because automatic rumor extraction is difficult. Extracting rumor-disaffirmation is easier than extracting the rumors themselves. We classify tweets in disaster situations, analyze tweets in disaster situations based on users' impressions and compare the spread of rumor tweets in a disaster situation to that in a normal situation.
Findings
The analysis results showed the following characteristics of rumors in a disaster situation. The information transmission is 74.9 per cent, representing the greatest number of tweets in our data set. Rumor tweets give users strong behavioral facilitation, make them feel negative and foment disorder. Rumors of a normal situation spread through many hierarchies but the rumors of disaster situations are two or three hierarchies, which means that the rumor spreading style differs in disaster situations and in normal situations.
Originality/value
The originality of this paper is to target rumors on Twitter and to analyze rumor characteristics by multiple aspects using not only rumor-tweets but also disaffirmation-tweets as an investigation object.
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James M. Forjan and Michael S. McCorry
In this paper, the link between stock distribution announcements and capital markets is examined. The results show that stock split announcements result in higher share prices and…
Abstract
In this paper, the link between stock distribution announcements and capital markets is examined. The results show that stock split announcements result in higher share prices and narrower percentage bid‐ask spreads, while stock dividend announcements have little effect on either prices or percentage spreads.
Shinichi Yamaguchi and Tsukasa Tanihara
In recent years, the social impact of misinformation has intensified. The purpose of this study is to clarify the mechanism by which misinformation spreads in society.
Abstract
Purpose
In recent years, the social impact of misinformation has intensified. The purpose of this study is to clarify the mechanism by which misinformation spreads in society.
Design/methodology/approach
Testing the following two hypotheses by a logit model analysis of survey data using actual fact-checked COVID-19 vaccine and political misinformation: people who believe that some misinformation is true are more likely to spread it than those who do not believe in its truthfulness; people with lower media and information literacy are more likely to spread misinformation than people with higher media and information literacy.
Findings
The two hypotheses are supported, and the trend was generally robust regardless of the method, whether the means of diffusion was social media or direct conversation.
Social implications
The authors derived the following four implications from the results: governments need to further promote media information literacy education; platform service providers should consider mechanisms to facilitate the spread and display of posts by people who are aware of misinformation; fact-checking should be further promoted; people should acquire information based on the assumption that people who believe in some misinformation tend to spread it more.
Originality/value
First, it quantitatively clarifies the relationship between misinformation, true/false judgements and dissemination behaviour. Second, it quantitatively clarifies the relationship between literacy and misinformation dissemination behaviour. Third, it conducts a comprehensive analysis of diffusion behaviours, including those outside of social media.
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Clement Ola Adekoya and Joseph Kehinde Fasae
The purpose of this paper is to investigate the social media application and the spread of COVID-19 infodemic in Nigeria.
Abstract
Purpose
The purpose of this paper is to investigate the social media application and the spread of COVID-19 infodemic in Nigeria.
Design/methodology/approach
A descriptive survey research design was used for this study. A total of 1,200 social media users, regardless of their professions, were randomly selected for the study betweenmid-June and July 2020. Stratified and purposive sampling techniques were used for this study. The questionnaire was designed using Google form and administered using WhatsApp and Telegram to social media users above 18 years old in Nigeria. The data generated was analyzed using descriptive (frequency count) and inferential (mean) statistics, and was presented in tables.
Findings
It was found that people make use of social media during COVID-19 pandemic for diverse reasons such as listening to announcement to be informed, knowing the necessary measures to take by those infected and spreading up-to-date information on the pandemic. Social media tools were highly used during the COVID-19 pandemic, especially WhatsApp and Zoom. Findings reflected that misinformation was spread on social media. This study also showed that the infodemic associated with COVID-19 is managed by confirming the source of the information before sharing it and trusting information from reliable sources.
Research limitations/implications
The result of this research will contribute to the body of knowledge on social media application, fake news and the spread of COVID-19 infodemic in Nigeria and beyond.
Practical implications
Infodemic is a disaster in the health sector. The spread of infodemic is capable of misleading people, losing trust in government, health providers and health regulatory authorities. This study will help social media users to know how to properly manage social media infodemic during a pandemic or any health-related situations.
Originality/value
This study is novel as it approaches fake news from a COVID-19 perspective. Very few articles emanate from the developing countries in this area. This was because most of the narrative around fake news previously centered around the Western occurrences such as the Iraqi invasion by the USA, the US presidential elections and BREXIT. COVID-19 has demonstrated that the developing world is not immune from fake news as well. This study, therefore, assessed the management of infodemic associated with COVID-19 in Nigeria.
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Xiao Meng, Chengjun Dai, Yifei Zhao and Yuan Zhou
This study aims to investigate the mechanism of the misinformation spread based on the elaboration likelihood model and the effects of four factors – emotion, topic, authority and…
Abstract
Purpose
This study aims to investigate the mechanism of the misinformation spread based on the elaboration likelihood model and the effects of four factors – emotion, topic, authority and richness – on the depth, breadth and structural virality of misinformation spread.
Design/methodology/approach
The authors collected 2,514 misinformation microblogs and 142,006 reposts from Weibo, used deep learning methods to identify the emotions and topics of misinformation and extracted the structural characteristics of the spreading network using the network analysis method.
Findings
Results show that misinformation has a smaller spread size and breadth than true news but has a similar spread depth and structural virality. The differential influence of emotions on the structural characteristics of misinformation propagation was found: sadness can promote the breadth of misinformation spread, anger can promote depth and disgust can promote depth and structural virality. In addition, the international topic, the number of followers, images and videos can significantly and positively influence the misinformation's spread size, depth, breadth and structural virality.
Originality/value
The influencing factors of the structural characteristics of misinformation propagation are clarified, which is helpful for the detection and management of misinformation.
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Alon Sela, Orit Milo, Eugene Kagan and Irad Ben-Gal
The purpose of this paper is to propose a novel method to enhance the spread of messages in social networks by “Spreading Groups.” These sub-structures of highly connected…
Abstract
Purpose
The purpose of this paper is to propose a novel method to enhance the spread of messages in social networks by “Spreading Groups.” These sub-structures of highly connected accounts intentionally echo messages between the members of the subgroup at the early stages of a spread. This echoing further boosts the spread to regions substantially larger than the initial region. These spreading accounts can be actual humans or social bots.
Design/methodology/approach
The paper reveals an interesting anomaly in information cascades in Twitter and proposes the spreading group model that explains this anomaly. The model was tested using an agent-based simulation, real Twitter data and questionnaires.
Findings
The messages of few anonymous Twitter accounts spread on average more than well-known global financial media groups, such as The Wall Street Journal or Bloomberg. The spreading groups (also sometimes called BotNets) model provides an effective mechanism that can explain these findings.
Research limitations/implications
Spreading groups are only one possible mechanism that can explain the effectiveness of spread of tweets from lesser known accounts. The implication of this work is in showing how spreading groups can be used as a mechanism to spread messages in social networks. The construction of spreading groups is rather technical and does not require using opinion leaders. Similar to the case of “Fake News,” we expect the topic of spreading groups and their aim to manipulate information to receive growing attention in public discussion.
Practical implications
While harnessing opinion leaders to spread messages is costly, constructing spreading groups is more technical and replicable. Spreading groups are an efficient method to amplify the spread of message in social networks.
Social implications
With the blossoming of fake news, one might tend to assess the reliability of news by the number of users involved in its spread. This heuristic might be easily fooled by spreading groups. Furthermore, spreading groups consisting of a blend of human and computerized bots might be hard to detect. They can be used to manipulate financial markets or political campaigns.
Originality/value
The paper demonstrates an anomaly in Twitter that was not studied before. It proposes a novel approach to spreading messages in social networks. The methods presented in the paper are valuable for anyone interested in spreading messages or an agenda such as political actors or other agenda enthusiasts. While social bots have been widely studied, their synchronization to increase the spread is novel.
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Yunfei Xing, Wu He, Gaohui Cao and Yuhai Li
COVID-19, a causative agent of the potentially fatal disease, has raised great global public health concern. Information spreading on the COVID-19 outbreak can strongly influence…
Abstract
Purpose
COVID-19, a causative agent of the potentially fatal disease, has raised great global public health concern. Information spreading on the COVID-19 outbreak can strongly influence people behaviour in social media. This paper aims to question of information spreading on COVID-19 outbreak are addressed with a massive data analysis on Twitter from a multidimensional perspective.
Design/methodology/approach
The evolutionary trend of user interaction and the network structure is analysed by social network analysis. A differential assessment on the topics evolving is provided by the method of text clustering. Visualization is further used to show different characteristics of user interaction networks and public opinion in different periods.
Findings
Information spreading in social media emerges from different characteristics during various periods. User interaction demonstrates multidimensional cross relations. The results interpret how people express their thoughts and detect topics people are most discussing in social media.
Research limitations/implications
This study is mainly limited by the size of the data sets and the unicity of the social media. It is challenging to expand the data sets and choose multiple social media to cross-validate the findings of this study.
Originality/value
This paper aims to find the evolutionary trend of information spreading on the COVID-19 outbreak in social media, including user interaction and topical issues. The findings are of great importance to help government and related regulatory units to manage the dissemination of information on emergencies, in terms of early detection and prevention.
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Jiakun Wang and Yun Li
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…
Abstract
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.
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Frank Heflin, Kenneth W. Shaw and John J. Wild
The purpose of this paper is to study the relation between financial analysts’ ratings of firms’ disclosure policies and the intraday pattern in spreads between specialists’ bid…
Abstract
Purpose
The purpose of this paper is to study the relation between financial analysts’ ratings of firms’ disclosure policies and the intraday pattern in spreads between specialists’ bid and ask price quotes.
Design/methodology/approach
Measure of the disclosure policy is based on financial analysts’ ratings of the quality of firms’ annual reports, quarterly and other information, and investor relations activities. The bid‐ask spread is the ask price minus the bid price. Time‐weighted bid‐ask spreads were measured over half‐hour trading intervals. Generalized method of moments is used to estimate regressions of bid‐ask spreads on disclosure policy ratings and controls for trading volume, price volatility, and share price.
Findings
It was found that spreads are uniformly lower for firms with higher‐rated disclosure policies in all half‐hour trading intervals during the day. In addition, increases in spreads in the first two half‐hours of trading are smaller for firms with higher‐rated disclosures. Finally, our evidence suggests spreads increase more in the last half‐hour of trading for firms with better disclosure policies, and subsequent tests suggest this is due to greater end‐of‐day liquidity trading.
Research limitations/implications
These results suggest that disclosure policy is a determinant of both the level and pattern of intraday bid‐ask spreads. Firms with higher‐rated disclosure policies have a more liquid market for their shares, which is theoretically linked to a lower cost of capital. In addition, better disclosure mitigates the decrease in market liquidity typically observed at the open of daily trading.
Practical implications
Better disclosures can help reduce market frictions.
Originality/value
This paper is the first to study the relation between disclosure policy and intraday spread patterns.
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