Information-sharing Behavior Research Articles

Self-Regulation of Internet Behaviors on Social Media Platforms

The current research sought a comprehensive understanding about the consequences of information-sharing behavior on social media, given public concerns about privacy violations. We used a mixed-methods approach to investigate the influence of the self on “revealing” and emotional “healing” experiences online. Respondents completed a survey measuring sense of self and motivations for using social media, as well as revealing and healing attitudes and behavior. We conducted a principal component factor analysis on separate parts of the survey and ran Pearson correlations of the emerging factors. Qualitative data describing experiences of online self-disclosure were used to illustrate the correlational findings. The “revealing” factors contrasted adaptive with maladaptive and naïve posting. The sense of self, as well as motivations for social media use, influenced whether users engaged in destructive posting behaviors. The “healing” factors were associated with positive motivations for self-disclosure, seeking a supportive online community, and building resilience. Correlational data revealed that respondents with an insecure or asocial sense of self felt the greater need for online self-disclosure. Motivations to self-disclose online and experiences of “healing”, with the help of a supportive online community, depended on whether the sense of self was secure, insecure, or asocial.

The uses and gratifications (U&G) model for understanding fake news sharing behavior on social media

BackgroundSocial networking sites (SNSs) have made information sharing easier than ever, this ease has also facilitated the spread of misinformation. ObjectiveTo ascertain and validate the uses and gratifications (U&G) factors associated with fake news-sharing behaviors on SNSs. MethodsA five-factor model based on the U&G theory was measured to estimate fake news-sharing behavior among university students, using the structural equation modeling. FindingsPassing time has a strong positive influence on fake news sharing behavior (β = 0.517, CR = 4.017, p < 0.001). Information seeking has a weak and non-significant positive influence on fake news sharing behavior (β = 0.308, CR = 1.569, p = 0.117). However, socialization (β = −0.164, CR = −1.883, p = 0.377), entertainment (β = −0.070, CR = −0.878, p = 0.380), and information sharing (β = −0.044, CR = −0.295, p = 0.768) gratifications have non-significant negative influences on fake news sharing behavior. The goodness-of-fit indices indicate that the proposed model is acceptable (χ2 = 2.195 df = 237; p < 0.001; GFI = 0.920; IFI = 0.901; CFI = 0.899; SRMR: 0.077; RMSEA = 0.049). ConclusionPassing time is the key predictor of fake news sharing behavior, while information-seeking gratification also contributes positively to this behavior. The study suggests several different approaches to prevent the spread of fake news, including implementing news literacy programs, installing a firewall, supporting fact-checking organizations, and implementing regulations and legislations for responsible social media practices. ImplicationsThe study is significant because it goes beyond the “what” of fake news sharing to understand the “why”. This deeper understanding can lead to more effective solutions for promoting responsible information-sharing behavior and combating the spread of fake news in the post-truth era.

Use &amp; Abuse of Personal Information, Part II: Robust Generation of Fake IDs for Privacy Experimentation

When personal information is shared across the Internet, we have limited confidence that the designated second party will safeguard it as we would prefer. Privacy policies offer insight into the best practices and intent of the organization, yet most are written so loosely that sharing with undefined third parties is to be anticipated. Tracking these sharing behaviors and identifying the source of unwanted content is exceedingly difficult when personal information is shared with multiple such second parties. This paper formulates a model for realistic fake identities, constructs a robust fake identity generator, and outlines management methods targeted towards online transactions (email, phone, text) that pass both cursory machine and human examination for use in personal privacy experimentation. This fake ID generator, combined with a custom account signup engine, are the core front-end components of our larger Use and Abuse of Personal Information system that performs one-time transactions that, similar to a cryptographic one-time pad, ensure that we can attribute the sharing back to the single one-time transaction and/or specific second party. The flexibility and richness of the fake IDs also serve as a foundational set of control variables for a wide range of social science research questions revolving around personal information. Collectively, these fake identity models address multiple inter-disciplinary areas of common interest and serve as a foundation for eliciting and quantifying personal information-sharing behaviors.

Can I trust my AI friend? The role of emotions, feelings of friendship and trust for consumers' information-sharing behavior toward AI

Research background: AI devices and robots play an increasingly important role in consumers’ everyday life, by accompanying the consumer all day long. This presence has several utilitarian and social benefits, but at the same time the optimal functioning of AI requires personal information from the consumer. Purpose of the article: Starting from the premise that people share more information with friends, we have tested empirically whether an emotional behavior of AI can evoke the same emotions in the relationship between consumers and their AI devices, leading to a higher self-disclosing behavior. Methods: To validate the proposed hypotheses, three mediation models were tested using structural equation modelling in Smart-PLS 3.3.3, based on data collected with the help of an online survey. Findings &amp; value added: We prove empirically that AI’s emotional behavior can increase consumers’ trust, it can evoke feelings of friendship and it can determine a higher perceived control over the shared private information, thus leading to lower perceived threats regarding the consumers’ vulnerability and exposure related to sharing of private data. These results have important implications for designing consumer-AI interactions.

Information and Electronic Transactions Law effects on Malang City people's information-sharing behavior

Information and Electronic Transactions Law effects on Malang City people's information-sharing behavior

Evaluating Social Media Information-sharing Behavior among Dhaka University Students: A Study

Evaluating Social Media Information-sharing Behavior among Dhaka University Students: A Study

Social media sharing disposition (SMSD) as a driver of consumer information-sharing behavior

Purpose 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. Design/methodology/approach 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. Findings 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. Research limitations/implications 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. Practical implications 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. Originality/value 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.

Determinants of users' unverified information sharing on social media platforms: A herding behavior perspective

The proliferation of unverified or false information by irresponsible users can significantly amplify the spread of misinformation or fake news. Despite growing research on unverified information sharing, a comprehensive understanding of the varying influences of different factors and strategies to mitigate this issue remains under investigation. To address this research gap, this study, rooted in the theory of herd behavior, develops, and tests a model theorizing the reasons behind social media users' unverified information sharing. Data was collected from 510 respondents across six regions of China using a convenience sampling method. The collected data was analyzed using Mplus. The results from this study indicated that perceived severity, state uncertainty, and herding have a significant positive influence on unverified information sharing. These results enrich the understanding of unverified information-sharing behavior among Chinese social media users. Drawing from these results, we suggest platform administrators and policymakers mitigate herd behavior tendencies and stem the spread of misinformation by disseminating timely, accurate, and authoritative information. Since this action will reduce users' perceptions of severity and uncertainty. Social media users are also advised to stay vigilant over the implications of herd behavior and foster a more critical attitude towards information sharing.

The Influence of Cognitive and Emotional Factors on Social Media Users' Information-Sharing Behaviours during Crises: The Moderating Role of the Construal Level and the Mediating Role of the Emotional Response.

Understanding the intricate dynamics of social media users' information-sharing behaviours during crises is essential for effective public opinion management. While various scholarly efforts have attempted to uncover the factors influencing information sharing through different lenses, the underlying mechanisms remain elusive. Building upon the heuristic-systematic model (HSM) and construal level theory (CLT), this study explores the complex mechanisms that govern social media users' information-sharing behaviours. The results indicate that both cognition and emotion play crucial roles in shaping users' information-sharing behaviours, with systematic cues having the most significant impact on information-sharing behaviours. In terms of heuristic cues, positive emotions are more influential on information-sharing behaviours than primary cognition and negative emotions. Furthermore, spatial distance emerges as a key moderator, influencing individuals' levels of engagement in information sharing. Emotion also acts as a mediator, connecting cognition to information sharing. This study provides insights into the sophisticated mechanisms of information sharing during crises, offering valuable implications for emergency management agencies to utilise social media for targeted public opinion guidance.

Exploring the social diffusion effects of green consumption: Evidence from green innovative products

In the context of mobile internet, the social diffusion effect of green consumption behavior becomes increasingly pronounced. This study, originating from the perspective of green consumption and grounded in the diffusion of innovation theory, constructs a model to analyze the impact of green consumption behavior on information-sharing behavior. The experience sampling method was utilized to collect 898 valid paired data points from 169 consumers, and Multilevel Structural Equation Modeling was applied to test the proposed model. The findings indicate a positive influence of green consumption behavior on information-sharing behavior, with perceived novelty and usefulness serving as mediators in this relationship. Moreover, the construal level moderates the impact of green consumption behavior on perceived novelty and usefulness. Further, at a high construal level, green consumption behavior enhances information-sharing behavior via its effect on perceived novelty, whereas at a low construal level, it does so through its impact on perceived usefulness.

Patient experiences of information-sharing and patient-centred care across the broad landscape of primary care practice and provision: a nationally representative survey of Australian adults

BackgroundAustralian government strategies and frameworks have been developed in recent years to encourage the integration and coordination of primary care delivery; including patient-centred approaches to clinical and preventative care, and health promotion. This study aims to explore patient experiences of information-sharing and patient-centred care across various primary care clinical settings, with a particular focus on clinical encounters with GPs, naturopaths, osteopaths and acupuncturists.MethodsData about healthcare utilisation and experiences from a 63-item cross-sectional survey obtained from a nationally representative sample of Australian adults aged ≥ 18 years were analysed. Chi-square and Kruskal-Wallis H tests were used to explore differences in the experiences of knowledge and information sharing during GP consultations among those who also consulted with a naturopath, osteopath or acupuncturist, compared those who had not. Logistic regression was used to investigate correlations between participants perceptions about GP consultation outcomes, and the GP’s information-sharing behaviour or perceived experience of patient-centredness.ResultsAcross 2354 participants, verbal explanation (76.3%) and/or individualised handouts (16.8%) were the most common type of information shared in GP consultations. Individuals who consulted with a GP and a naturopath, an osteopath, or an acupuncturist reported a lower rate of receiving a verbal explanation from their GP but higher rate of receiving other types of information sources including handouts. Over one quarter of study participants who visited a GP did not discuss any of their health information with their GP. Information sharing was lower for individuals who also visited a naturopath, osteopath or acupuncturist. Participants scored their consultations with a GP as patient-centred, but these scores were lower among participants who also consulted with at least one other primary care practitioner type included in the study.ConclusionsPublic health and health services researchers, policymakers and leaders of primary care professions have a role and responsibility to ensure practitioners are confident and competent in sharing health information with their patients that considers their health literacy needs, and the importance of patient-centred care. Research focussed on a more in-depth understanding of the differences and relationships observed across the primary care landscape in this study is recommended.

Influence of Social Media on Information Seeking and Sharing Behavior among Young Adults in Kenya

Purpose: The aim of the study was to investigate the influence of social media on information seeking and sharing behavior among young adults in Kenya.&#x0D; Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.&#x0D; Findings: Social media heavily influences information seeking and sharing behavior among young adults in Kenya, facilitating quick access to diverse content despite concerns about reliability. To address misinformation and promote digital literacy, implementing educational programs and establishing guidelines for verifying information on social platforms are recommended.&#x0D; Unique Contribution to Theory, Practice and Policy: Uses and gratifications theory, social cognitive theory &amp; diffusion of innovations theory may be used to anchor future studies on influence of social media on information seeking and sharing behavior among young adults in Kenya. Develop and implement digital literacy programs tailored to the needs of young adults in Kenya, with a focus on enhancing critical evaluation skills, media literacy, and information verification techniques. Advocate for the development of policies and guidelines to regulate the dissemination of misinformation, hate speech, and harmful content on social media platforms, while preserving freedom of expression and information sharing.

Users' unverified information-sharing behavior on social media: The role of reasoned and social reactive pathways

Unverified or false information spread by irresponsible users can amplify the dissemination of fake news or misinformation. This phenomenon may not only undermine the credibility of social media platforms but also pose severe consequences for individuals and society. This study applies and extends the prototypical willingness model with the aim of comprehending the reasons, and decision-making process driving users' unverified information-sharing behavior a reasoned and intended pathway or an impulsive and unconscious one. Data from a sample of 646 users were analyzed using Structural Equation Modeling to assess the determinative effect of both the reasoned pathway (attitude toward unverified information-sharing, subjective norm, and perceived behavioral control) and the social-reaction pathway (prototype favorability and similarity). Findings highlight the substantial role of the social-reaction pathway in forecasting users' unverified information-sharing behavior, with prototype similarity and attitude being the dominant predictors. Meanwhile, components of the reasoned pathway, specifically perceived behavior control, and attitude, also exhibited significant contributions toward predicting the behavior. In summary, while a deliberate, reasoned process has some influence, the sharing of unverified information on social media by users is primarily an intuitive, spontaneous response to specific online circumstances. This study therefore offers valuable insights that could aid relevant stakeholders in effectively regulating the spread of misinformation. Against this backdrop, highlighting potential risks associated with sharing unverified information and the negative portrayal of users propagating misinformation may contribute to the development of a more critical perspective toward online information sharing by users themselves.

Modelling the dual dynamic traffic flow evolution with information perception differences between human-driven vehicles and connected autonomous vehicles

The introduction of connected autonomous vehicles (CAVs) potentially improves the link capacity and backward wave speed of traffic flow, while the advanced communication technology could well make it possible to allow CAV users to share their travel information. To bridge the knowledge gaps in the network evolution under mixed environment of human-driven vehicles (HVs) and CAVs, it is essential to explore multi-dimensional dynamic traffic assignment. An inertia-based multi-class dual dynamic traffic assignment (IMDDTA) model is proposed to capture the intraday and diurnal variations of the mixed traffic flow under the disequilibrium state simultaneously. Specifically, in this study we consider the inertia of HV users as well the information-sharing behaviour of CAV users respectively, characterized by different extensions of the multinomial logit (MNL) model. To demonstrate the properties of the model, two numerical case studies are conducted based on the Braess network and the Sioux Falls network. The results indicate an acceptable validity and applicability of the model and provide valuable insights on the evolution of traffic flow under mixed environment.

“In this together”: on the antecedents and implications of crowdfunding community identification and trust

ABSTRACT Despite references to crowdfunding as a community-embedded phenomenon, few studies explore the antecedents and implications of crowdfunding communities. This study suggests community identification and trust as two core aspects of crowdfunding communities, while aiming to identify their antecedents and implications for crowdfunding campaign information-sharing intentions and behavior. Information-sharing is a necessary condition for successful entrepreneurial fundraising when using crowdfunding. For this purpose, we use survey data collected from users of Finland’s leading reward crowdfunding website, Mesenaatti.me, while analyzing it using structural equation modelling. Our findings show that community identification and trust are both positively associated with crowdfunding contribution attitudes and with information-sharing intentions. However, only community identification is associated with information-sharing behaviors. Enjoyment, homophily, and community outcome expectations are antecedents of both community identification and trust. Tie strength and normative pressures are antecedents of community identification. Finally, information-sharing intentions mediate the effect of community trust on information-sharing behavior. We discuss explanations for these findings and their implications for crowdfunding research and practice.

Privacy Concerns About Sharing General and Specific Health Information on Twitter: Quantitative Study.

Twitter is a common platform for people to share opinions, discuss health-related topics, and engage in conversations with a wide audience. Twitter users frequently share health information related to chronic diseases, mental health, and general wellness topics. However, sharing health information on Twitter raises privacy concerns as it involves sharing personal and sensitive data on a web-based platform. This study aims to adopt an interactive approach and develop a model consisting of privacy concerns related to web-based vendors and web-based peers. The research model integrates the 4 dimensions of concern for information privacy that express concerns related to the practices of companies and the 4 dimensions of peer privacy concern that reflect concerns related to web-based interactions with peers. This study examined how this interaction may affect individuals' information-sharing behavior on Twitter. Data were collected from 329 Twitter users in the United States using a web-based survey. Results suggest that privacy concerns related to company practices might not significantly influence the sharing of general health information, such as details about hospitals and medications. However, privacy concerns related to companies and third parties can negatively shape the disclosure of specific health information, such as personal medical issues (β=-.43; P<.001). Findings show that peer-related privacy concerns significantly predict sharing patterns associated with general (β=-.38; P<.001) and specific health information (β=-.72; P<.001). In addition, results suggest that people may disclose more general health information than specific health information owing to peer-related privacy concerns (t165=4.72; P<.001). The model explains 41% of the variance in general health information disclosure and 67% in specific health information sharing on Twitter. The results can contribute to privacy research and propose some practical implications. The findings provide insights for developers, policy makers, and health communication professionals about mitigating privacy concerns in web-based health information sharing. It particularly underlines the importance of addressing peer-related privacy concerns. The study underscores the need to build a secure and trustworthy web-based environment, emphasizing the significance of peer interactions and highlighting the need for improved regulations, clear data handling policies, and users' control over their own data.

Emotions and Information Diffusion on Social Media: A Replication in the Context of Political Communication on Twitter

This paper presents a methodological and conceptual replication of Stieglitz and Dang-Xuan’s (2013) investigation of the role of sentiment in information-sharing behavior on social media. Whereas Stieglitz and Dang-Xuan (2013) focused on Twitter communication prior to the state parliament elections in the German states Baden-Wurttemberg, Rheinland-Pfalz, and Berlin in 2011, we test their theoretical propositions in the context of the state parliament elections in Saxony-Anhalt (Germany) 2021. We confirm the positive link between sentiment in a political Twitter message and its number of retweets in a methodological replication. In a conceptual replication, where sentiment was assessed with the alternative dictionary-based tool LIWC, the sentiment was negatively associated with the retweet volume. In line with the original study, the strength of association between sentiment and retweet time lag insignificantly differs between tweets with negative sentiment and tweets with positive sentiment. We also found that the number of an author’s followers was an essential determinant of sharing behavior. However, two hypotheses supported in the original study did not hold for our sample. Precisely, the total amount of sentiments was insignificantly linked to the time lag to the first retweet. Finally, in our data, we do not observe that the association between the overall sentiment and retweet quantity is stronger for tweets with negative sentiment than for those with positive sentiment.

Information security risks and sharing behavior on OSN: the impact of data collection awareness

PurposeThis study aims to ascertain the impact of data collecting awareness on perceived information security concerns and information-sharing behavior on social networking sites.Design/methodology/approachBased on communication privacy management theory, the study forecasted the relationship between information-sharing behavior and awareness of data collecting purposes, data collection tactics and perceived security risk using structural equation modeling analysis and one-way ANOVA. The sample size of 521 young social media users in Vietnam, ages 18 to 34, was made up of 26.7% men and 73.3% women. When constructing the questionnaire survey method with lone source respondents, the individual’s unique awareness and experiences with using online social networks (OSNs) were taken into account.FindingsThe results of the investigation demonstrate a significant relationship between information-sharing and awareness of data collecting, perceptions of information security threats and behavior. Social media users have used OSN privacy settings and paid attention to the sharing restriction because they are concerned about data harvesting.Research limitations/implicationsThis study was conducted among young Vietnamese social media users, reflecting specific characteristics prevalent in the Vietnamese environment, and hence may be invalid in other nations’ circumstances.Practical implicationsSocial media platform providers should improve user connectivity by implementing transparent privacy policies that allow users to choose how their data are used; have clear privacy statements and specific policies governing the use of social media users’ data that respect users’ consent to use their data; and thoroughly communicate how they collect and use user data while promptly detecting any potential vulnerabilities within their systems.Originality/valueThe authors ascertain that the material presented in this manuscript will not infringe upon any statutory copyright and that the manuscript will not be submitted elsewhere while under Journal of Information, Communication and Ethics in Society review.

Impact of Appraisal Concerns on Marketing Information Sharing Behavior in Social Commerce: Integrating User Emotions and System Feedback Dynamics

This study, grounded in the theory of evaluation apprehension, aims to develop a comprehensive model that integrates user psychology, emotional dynamics, and system functionalities to examine user behavior in marketing information sharing. A methodological blend of online surveys and offline lab experiments is employed to explore the obstructive role of evaluation apprehension in the dynamics between perceived sharing value and the behavior of sharing marketing information. Additionally, the study investigates the operational mechanism of system feedback attributes - a distinct system characteristic - in the user sharing process, specifically focusing on its moderating effect on the inhibitory influence of evaluation apprehension. On a practical note, it provides strategic insights for businesses from the angles of user psychology, reward mechanism design, and system architecture to encourage more active user participation in sharing marketing information.

Determinants of American Adults' Use of Digital Health and Willingness to Share Health Data to Providers, Family, and Social Media: A Cross-sectional Study.

With the global pandemic driving the adoption of digital health, understanding the predictors or determinants of digital health usage and information sharing gives an opportunity to advocate for broader adoption. We examined the prevalence and predictors of digital health usage and information-sharing behaviors among American adults. Data were from the Health Information National Trends Survey 5 Cycle 4. More than two-thirds used a digital resource for health-related activities (eg, to check test results). About 81% were willing to share their digital data with their provider, 75% with family, and 58% with friends. Only 14% shared health information on social media. Gender, education, device types, and performance expectancy of digital health were common factors associated with both digital health usage and information-sharing behaviors. Other predictors included rurality, patient portal access, income, and having a chronic disease. Of note, we found that Asian American Pacific Islanders, compared with Whites, were less likely to share information with providers. Performance expectancy was a significant determinant of information sharing. Those diagnosed with diabetes were 4% less likely to share information with their providers. With the growing digital divide, there is a need to advocate for more usable and accessible digital health to assist with person-centered care.