Information Processing and Management, volume 57, issue 1, pages 102128

Voluntary sharing and mandatory provision: Private information disclosure on social networking sites

Publication typeJournal Article
Publication date2020-01-01
scimago Q1
wos Q1
SJR2.134
CiteScore17.0
Impact factor7.4
ISSN03064573, 18735371
Computer Science Applications
Library and Information Sciences
Information Systems
Management Science and Operations Research
Media Technology
Abstract
Private information disclosure on social networking sites (SNS) is one of the most important and active issues in the information management arena. The growing phenomenon of platforms requiring users to disclose personal information exposes the limitations of previous studies that only focus on users’ voluntary disclosure. In this study, we define two modes of users’ private information disclosure behavior: voluntary sharing and mandatory provision. Using the Communication Privacy Management theory, we built a framework to explain the impact of individual characteristics, context, motivation, and benefit–risk ratio on the user's willingness to disclose voluntarily or mandatorily. Our research shows that voluntary sharing is more likely to be driven by positive factors, such as perceived benefits, social network size, and personalization, while mandatory provision is affected by individual characteristics such as age, privacy policy, and perceived risks. One of our interesting findings is that perceived risk has less impact on voluntary sharing than previous studies suggested. When encouraging users to share information voluntarily, platforms do not need to pay as much attention to reducing perceived risk as in the mandatory providing mode, but should focus on improving perceived benefits. Being the first to classify and compare the private information disclosure modes of SNS users, our research enriches the existing literature and opens up new avenues for researchers and social networking platforms.
Zhang S., Kwok R.C., Lowry P.B., Liu Z., Wu J.
Information and Management scimago Q1 wos Q1
2019-11-01 citations by CoLab: 36 Abstract  
There is a growing body of research about the influence of users’ perceived stress on their social networking site (SNS) usage behaviors. In general, stress negatively leads to a reduction in SNS usage (e.g., discontinuous use and self-disclosure). However, very little research has examined how SNS users strive to resolve stress problems from a positive perspective. To fill this gap, we conducted a research study among users of Moments, a large SNS in China. Based on the conservation of resources (COR) theory, we hypothesized that SNS users’ response to role stress, a subtype of stress, might be positive, leading to investments in social resources (e.g., motivation for relationship maintenance and self-presentation) and generating an increased level of self-disclosure on SNS. The survey results revealed the mediating effect of motivation for relationship maintenance and self-presentation on the SNS stress–disclosure relationship. We found that SNS users conserve their resources by maintaining relationships and presenting themselves positively in response to role stress, as predicted. Theoretical contributions and practical implications of the study are discussed, as are its limitations and directions for future research.
Tifferet S.
Computers in Human Behavior scimago Q1 wos Q1
2019-04-01 citations by CoLab: 93 Abstract  
The purpose of this study was to assess the presence and magnitude of gender differences in privacy-seeking tendencies on social network sites (SNS). To do so, a meta-analytic approach was chosen. A literature review produced a sample of 61 effect sizes from 37 independent studies (N = 16,159,261). Results showed that females on social network sites displayed higher privacy concerns and behaviors than did males. The gender differences, while all pointing to females being more committed to enhancing privacy, were small and statistically heterogeneous. A clear gender difference was apparent for activating privacy settings (d = 0.35) and untagging photographs (d = 0.26), whereas privacy concerns (d = 0.13) and disclosure of personal information (d = 0.13) showed smaller gender differences. The findings are in line with both evolutionary and social role theories and may be explained by differences in personality, threat vulnerability, or SNS activity levels. Advocators of SNS privacy should target males as the more vulnerable segment to privacy breaches. Additional studies are needed to investigate the moderating effects of variables such as culture and age, and to clarify the basis of this gender difference.
McNealy J., Mullis M.D.
Computers in Human Behavior scimago Q1 wos Q1
2019-03-01 citations by CoLab: 17 Abstract  
The friction and interplay between information and privacy, personal boundaries, and control and ownership of information is central to communication privacy management theory (CPM). In this autoethnographic study of the online gossip forum Lipstick Alley, CPM provides a framework for investigating how gender and culture shape boundaries and information sharing. The three CPM boundary coordination rules, linkage, ownership, and permeability, were found to be present and influenced how gossip forum users share, managed, and discussed the information on the site. Findings suggest that gender and culture play a significant role in shaping the kind of information shared. Further, ideas about the ownership of information shaped rules about how information should be managed and the consequences for failing to do so.
Widjaja A.E., Chen J.V., Sukoco B.M., Ha Q.
Computers in Human Behavior scimago Q1 wos Q1
2019-02-01 citations by CoLab: 42 Abstract  
Despite prevalent privacy and security threats on the cloud, users have put tremendous amounts of their personal information on cloud storage. This present study proposes a comprehensive research framework to investigate cloud storage users' willingness to put personal information on personal cloud-based storage applications. Our research framework is theoretically derived from the Communication Privacy Management Theory and Privacy-Trust-Behavioral Intention Model. To empirically test our research framework, we conducted an online survey of 786 active cloud storage users both in Indonesia and Taiwan. The findings suggest that cloud storage users' willingness to put personal information is highly influenced by trust, perceived costs, perceived benefits, and also the degree of sensitivity of the personal information. Some findings with regard to cultural differences between the two countries are also showed out. The key findings, implications, and limitations are discussed in this paper. • Trust influences cloud storage users' willingness to put personal information. • Perceived cost is more apparent when users put more sensitive personal information. • Perceived benefit is more apparent when users put less sensitive personal information. • Institutional privacy assurances are not effective in reducing perceived cost. • Culture influences users' perceptions of privacy in context of cloud storage.
Liu Z., Wang X.
Information and Management scimago Q1 wos Q1
2018-12-01 citations by CoLab: 62 Abstract  
Individuals presently interact with their diverse social circles on social networking sites and may find it challenging to maintain their privacy while deriving pleasure through self-disclosure. Drawing upon the communication privacy management theory, our study examines how boundary coordination and boundary turbulence can influence individuals’ self-disclosure decisions. Further, our study examines how the effects of boundary coordination and boundary turbulence differ across cultures. Our hypotheses are tested with survey data collected from the United States and China. The results strongly support our hypotheses and show interesting cultural differences. The implications for theory and practice are discussed.
Zarrinkalam F., Kahani M., Bagheri E.
2018-03-01 citations by CoLab: 78 Abstract  
Inferring users’ interests from their activities on social networks has been an emerging research topic in the recent years. Most existing approaches heavily rely on the explicit contributions (posts) of a user and overlook users’ implicit interests, i.e., those potential user interests that the user did not explicitly mention but might have interest in. Given a set of active topics present in a social network in a specified time interval, our goal is to build an interest profile for a user over these topics by considering both explicit and implicit interests of the user. The reason for this is that the interests of free-riders and cold start users who constitute a large majority of social network users, cannot be directly identified from their explicit contributions to the social network. Specifically, to infer users’ implicit interests, we propose a graph-based link prediction schema that operates over a representation model consisting of three types of information: user explicit contributions to topics, relationships between users, and the relatedness between topics. Through extensive experiments on different variants of our representation model and considering both homogeneous and heterogeneous link prediction, we investigate how topic relatedness and users’ homophily relation impact the quality of inferring users’ implicit interests. Comparison with state-of-the-art baselines on a real-world Twitter dataset demonstrates the effectiveness of our model in inferring users’ interests in terms of perplexity and in the context of retweet prediction application. Moreover, we further show that the impact of our work is especially meaningful when considered in case of free-riders and cold start users.
Xu H., Dinev T., Smith J., Hart P.
2018-02-04 citations by CoLab: 379 Abstract  
Organizational information practices can result in a variety of privacy problems that can increase consumers’ concerns for information privacy. To explore the link between individuals and organizations regarding privacy, we study how institutional privacy assurances such as privacy policies and industry self-regulation can contribute to reducing individual privacy concerns. Drawing on Communication Privacy Management (CPM) theory, we develop a research model suggesting that an individual’s privacy concerns form through a cognitive process involving perceived privacy risk, privacy control, and his or her disposition to value privacy. Furthermore, individuals’ perceptions of institutional privacy assurances -namely, perceived effectiveness of privacy policies and perceived effectiveness of industry privacy self-regulation -are posited to affect the riskcontrol assessment from information disclosure, thus, being an essential component of privacy concerns. We empirically tested the research model through a survey that was administered to 823 users of four different types of websites: 1) electronic commerce sites, 2) social networking sites, 3) financial sites, and 4) healthcare sites. The results provide support for the majority of the hypothesized relationships. The study reported here is novel to the extent that existing empirical research has not explored the link between individuals’ privacy perceptions and institutional privacy assurances. We discuss implications for theory and practice and provide suggestions for future research.
Lin X., Featherman M., Sarker S.
Information and Management scimago Q1 wos Q1
2017-04-01 citations by CoLab: 169 Abstract  
Social networking sites (SNSs) have attracted more and more people to interact on line. Because of their popularity, firms and organizations are now marketing their business on SNS pages. It is essential for both SNS providers and firms to retain their current members. Consequently, use continuity of SNSs has gained the attention of both practitioners and researchers. However, few studies have systematically examined gender differences in such a context. To address this gap, we have developed an advanced framework to explain and analyze gender differences in users SNS continuance decisions. We propose an SNS continuance model by integrating SNS-oriented constructs (perceived privacy risk, perceived enjoyment, perceived reputation, and community identification) into the established ECM-ISC model and introduce gender as a key moderator. Our research results indicate that all the added SNS-oriented constructs influence users SNS continuance directly and indirectly. Furthermore, the impact of each factor on SNS continuance varies by gender. Each gender bases SNS continuance decisions on a different set of factors and/or different weights of the same factors. This study provides evidence that gender effects should be considered in understanding the continued usage of SNSs. It also provides an opportunity to develop a deeper understanding of gender differences in SNS continuance and fills the research gap regarding this. The theoretical and practical implications of these results are discussed.
Park J.
2014-05-01 citations by CoLab: 59 Abstract  
Social networking sites (SNSs) enable user to personalize their contents and functions. This feature has been assumed as causing positive effects on the use of online information services through enhancing user satisfaction. However, unlike other online information services (non-participatory information services), due to the results of personalization in a certain situation, SNS users cannot help using the SNS even though they feel dissatisfaction on using it. SNSs are different from other information services in the sense that they create and sustain their own value based on the number of participating members. In SNSs, personalization, reflected by updates and maintenance of profile pages, results in such participation. This study hypothesizes that personalization influences on the continued use of SNSs through two factors: switching cost (extrinsic factor) and satisfaction (intrinsic factor). Web-based survey was conducted with the samples of 677 SNS users from six universities in the US. In-person interviews were conducted with 25 university students to elicit their thoughts on the SNSs. Quantitative analysis employed by testing the proposed model with five hypotheses through a structural equation modeling (SEM) technique. The transcribed interview data was analyzed following the constant comparative technique. The main findings indicate that, as expected, the personalization increases its switching cost as well as satisfaction, which results in further use of SNSs. These findings suggest that it is necessary to consider both extrinsic and intrinsic factors of user perceptions when adding personalization features on SNSs.
Chakraborty R., Vishik C., Rao H.R.
Decision Support Systems scimago Q1 wos Q1
2013-11-01 citations by CoLab: 96 Abstract  
Social media are being fast adopted by older adults for extending their social relationships. However along with the adoption, there have been concerns about risky issues regarding privacy leakages and information sharing hazards. Such risks are partially due to the fact that seniors (knowingly or unknowingly) share private information that may be misused by others. In this paper we explore the privacy-preserving actions regarding information sharing for this demography on one social media platform - Facebook. Facebook is the largest social networking platform today and many of its privacy related practices have been in the news recently. More specifically, we study the information sharing behavior of the elderly by observing the extent to which they opt out of sharing information publicly about themselves on their profile pages. In addition, we also observe how much overlap exists between these older Facebook users and their respective friends in terms of their public information sharing habits and explore the differences across gender. Finally for comparative purposes we also collect data on a sample of younger Facebook users and conduct an analysis.
Litt E.
Computers in Human Behavior scimago Q1 wos Q1
2013-07-01 citations by CoLab: 125 Abstract  
Every day hundreds of millions of people log into social network sites and deposit terabytes of data as they share status updates, photographs, and more. This article explores how background factors, motivations, and social network site experiences relate to people's use of social network site technology to protect their privacy. The findings indicate that during technology-mediated communication on social network sites, not only do traditional privacy factors relate to the technological boundaries people enact, but people's experiences with the mediating technology itself do, too. The results also identify privacy inequalities, in which certain groups are more likely to take advantage of the technology to protect their privacy-suggesting that some individuals' information and reputations may be more at risk than others'.
Taddei S., Contena B.
Computers in Human Behavior scimago Q1 wos Q1
2013-05-01 citations by CoLab: 185 Abstract  
A number of studies have examined the relationship between privacy concerns, perceived control over information, trust and online self-disclosure, highlighting different points of view to understand this connection. This paper intends to compare these different models of explanation for self-disclosure behaviors in online social networks. Three different hypotheses are verified, using mediation and moderation analyses. The results allow underling the effect of the interaction between privacy concerns and trust on online self-disclosure, along with the absence of a direct influence of privacy concerns on disclosure itself. The results suggest practical implications for online social network providers, most of all with regard to privacy policies in online environments.
Zhao L., Lu Y., Gupta S.
2012-07-06 citations by CoLab: 176 Abstract  
Although location-based social network (LBSN) services have developed rapidly in recent years, the reasons why people disclose location-related information under this environment have not been adequately investigated. This study builds a privacy calculus model to investigate the factors that influence LBSN users' intention to disclose location-related information in China. In addition, this study applies justice theory to investigate the role of privacy intervention approaches used by LBSN Web sites in enhancing users' perception of justice, including incentives provision, interaction promotion, privacy control, and privacy policy. Model testing using structural equation modeling reveals that perceived cost (users' privacy concerns) and perceived benefits (personalization and connectedness) influence intention to disclose location-related information. Meanwhile, providing incentives and promoting interaction enhance, respectively, personalization and connectedness. Privacy control and privacy policies both help in reducing privacy concerns. We also find that individuals' awareness of Internet privacy legislation negatively influences privacy concerns, whereas previous privacy invasions do not. Finally, we find that personal innovativeness significantly influences intention to disclose location-related information. This study not only extends the privacy research on social networking sites under mobile environments but also provides practical implications for service providers and policy makers to develop better LBSNs.
Park Y.J.
Communication Research scimago Q1 wos Q1
2011-08-23 citations by CoLab: 252 Abstract  
This study examined the impact of three dimensions of digital literacy on privacy-related online behaviors: (a) familiarity with technical aspects of the Internet, (b) awareness of common institutional practices, and (c) understanding of current privacy policy. Hierarchical regression models analyzed data from a national sample of 419 adult Internet users. The analyses showed strong predictive powers of user knowledge, as indicated by the three discrete dimensions, on privacy control behavior. However, the findings were mixed when accounting for the interaction between knowledge and Internet experiences. There were limitations on the extents of knowledge and action related to personalized information. Furthermore, those limitations divided with sociodemographic characteristics such as age, gender, income, and education. Ramifications for the current status of the FTC policy are discussed.
Craciun G., Zhou W.
Journal of Consumer Marketing scimago Q1 wos Q2
2025-01-07 citations by CoLab: 0 Abstract  
Purpose In light of increasing public concern over social media privacy breaches, this study aims to unveil the context-dependent and individual-specific nature of social media disclosure decisions. In particular, this paper aims to examine the disclosure choices of maximizers and satisficers in the presence of privacy setting defaults on social networking sites (SNSs). Design/methodology/approach Data are collected through an online scenario-based experiment with 200 Mechanical Turk participants. The study uses a 2 (Privacy setting default: No Sharing [“Only Me”] vs. Public Sharing [“Everyone”]) × 2 (Decision mindset: maximizing vs. satisficing) between-subject design. Findings Analyzing responses using ordered logistic regression models, this paper found a general tendency toward default settings, with maximizers exhibiting a stronger default preference than satisficers. For instance, maximizers were eight times more likely, and satisficers were only three times more likely to choose “Everyone” in the presence of the “Everyone” (vs. “Only Me”) default when deciding who can post on their private page. The perceived level of privacy risk further shaped satisficers and maximizers’ preferences. Originality/value This study explores the impact of decision mindset on SNS privacy settings. It demonstrates that decision mindset moderates default preferences, revealing that maximizers show a higher default preference than satisficers. The research also highlights the interplay between default preferences and the compromise effect, contributing to the understanding of cognitive biases in privacy decisions. This paper offers insights for better privacy management and education strategies.
Al-Emran M., Al-Sharafi M.A., Foroughi B., Iranmanesh M., Alsharida R.A., Al-Qaysi N., Ali N.
Computers in Human Behavior scimago Q1 wos Q1
2024-10-01 citations by CoLab: 4 Abstract  
While offering novel user experiences, the Metaverse introduces complex cybersecurity challenges due to the sophisticated interaction of augmented reality (AR), virtual reality (VR), and web technologies. Addressing the barriers to cybersecurity behavior is essential to protect users against risks such as identity theft and loss of digital assets. Therefore, this research aims to investigate these barriers by developing a theoretical model that draws factors from the Technology Threat Avoidance Theory (TTAT) and considers variables such as privacy concerns, perceived risks, and response costs. The data were collected from 395 Metaverse users and were analyzed using the Partial Least Squares-Structural Equation Modeling (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA). The PLS-SEM findings showed that perceived threats, privacy concerns, and response costs have a significant negative impact on cybersecurity behavior, while perceived risks have an insignificant negative influence. The fsQCA results revealed that there is not a single pathway leading to robust cybersecurity behavior. Instead, eight configurations that include the presence and absence of certain conditions can lead to this desirable outcome. The findings not only advance the academic conversation on Metaverse security but also offer actionable strategies for stakeholders to reinforce user protection in this dynamic virtual environment.
Yan R., Gong X., Xu H., Yang Q.
Internet Research scimago Q1 wos Q1
2024-06-18 citations by CoLab: 0 Abstract  
PurposeA wealth of studies have identified numerous antecedents to online self-disclosure. However, the number of competing theoretical perspectives and inconsistent findings have hampered efforts to obtain a clear understanding of what truly influences online self-disclosure. To address this gap, this study draws on the antecedent-privacy concern-outcome (APCO) framework in a one-stage meta-analytical structural equation modeling (one-stage MASEM) study to test a nomological online self-disclosure model that assesses the factors affecting online self-disclosure.Design/methodology/approachUsing the one-stage MASEM technique, this study conducts a meta-analysis of online self-disclosure literature that comprises 130 independent samples extracted from 110 articles reported by 53,024 individuals.FindingsThe results reveal that trust, privacy concern, privacy risk and privacy benefit are the important antecedents of online self-disclosure. Privacy concern can be influenced by general privacy concern, privacy experience and privacy control. Furthermore, moderator analysis indicates that technology type has moderating effects on the links between online self-disclosure and some of its drivers.Originality/valueFirst, with the guidance of the APCO framework, this study provides a comprehensive framework that connects the most relevant antecedents underlying online self-disclosure using one-stage MASEM. Second, this study identifies the contextual factors that influence the effectiveness of the antecedents of online self-disclosure.
Zhang X., Cai Y., Liu F., Zhou F.
Kybernetes scimago Q1 wos Q2
2024-06-11 citations by CoLab: 0 Abstract  
PurposeThis paper aims to propose a solution for dissolving the “privacy paradox” in social networks, and explore the feasibility of adopting a synergistic mechanism of “deep-learning algorithms” and “differential privacy algorithms” to dissolve this issue.Design/methodology/approachTo validate our viewpoint, this study constructs a game model with two algorithms as the core strategies.FindingsThe “deep-learning algorithms” offer a “profit guarantee” to both network users and operators. On the other hand, the “differential privacy algorithms” provide a “security guarantee” to both network users and operators. By combining these two approaches, the synergistic mechanism achieves a balance between “privacy security” and “data value”.Practical implicationsThe findings of this paper suggest that algorithm practitioners should accelerate the innovation of algorithmic mechanisms, network operators should take responsibility for users’ privacy protection, and users should develop a correct understanding of privacy. This will provide a feasible approach to achieve the balance between “privacy security” and “data value”.Originality/valueThese findings offer some insights into users’ privacy protection and personal data sharing.
Gou Y., Li R., Zhuang Z.
Library Hi Tech scimago Q1
2024-06-11 citations by CoLab: 0 Abstract  
PurposeThis paper aims to objectively present the research dynamics of China in the field of information behavior and its development trends. Firstly, it incorporates China’s research in the field of information behavior into the global research network of information behavior, analyzing the changes in the status of Chinese scholars and their research institutions in the global research network from 1991 to 2022, the trends in publication volume and the cooperation relationships with other countries. Then, it conducts a detailed analysis of China’s research categories, groups, theoretical models and hot topics in different information contexts in the past five years (2018–2022).Design/methodology/approachThe study retrieved research literature related to information behavior in China from 1991 to 2022 in the Web of Science database. It then utilized a national/institutional cooperation network map to analyze the changes in the status of Chinese scholars/institutions in the global research network during this period, publication volume trends and cooperation relationships with other countries. Furthermore, it employed keyword co-occurrence network maps to analyze the key categories, groups, theories and models of China’s research in different information contexts in the past five years. Based on this, it used keyword clustering network maps to analyze the hot topics of China’s research in different information contexts in the past five years.Findings(1) China’s research in the field of information behavior started relatively late, but the volume of publications has grown rapidly since 2004, currently ranking second globally in cumulative publication quantity. However, the influence of the literature published by China is limited, and there is a lack of research institutions with global influence. (2) In the last five years, China has conducted extensive research in various information contexts. Among these, most research was conducted in work contexts, followed by healthcare contexts, especially studies related to epidemics. (3) Current research on information behavior in China is characterized by expanded and refined research groups, diversified research categories, continuous expansion and enrichment of research contexts, increased interdisciplinary nature of research and continuous innovation in research methods and theoretical models.Originality/valueThis study, utilizing a scientific knowledge map, elucidates China’s position in global information behavior research, with a specific emphasis on analyzing China’s research hot topics and trends in this field over the past five years. It aims to provide valuable resources for scholars interested in understanding the status of information behavior research in China and to offer some guidance for scholars currently or intending to engage in information behavior research.
Wang J., Cao Q., Zhu X.
Library Hi Tech scimago Q1
2024-05-22 citations by CoLab: 0 Abstract  
PurposeThis study aims to examine the effects of multidimensional factors of platform features, group effects and emotional attitudes on social media users’ privacy disclosure intention.Design/methodology/approachThis study collected the data from 426 respondents through an online questionnaire survey and conducted two approaches of structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) for theoretical hypothesis testing and configuration analysis of the data.FindingsThe results show that social media platform features (rewards of information disclosure, personalized service quality and data transparency), group effects (group similarity, group information interaction and network externality), individual emotional attitudes (trust and privacy concern) and control variable (gender) have a significant impact on privacy disclosure intention, as well as trust and privacy concern play mediating roles. Additionally, the fsQCA method reveals five causal configurations that explain high privacy disclosure intentions. Furthermore, the study reveals that male users pay more attention to platform features, while female users are more inclined to group effects.Originality/valueThis study attempts to construct a comprehensive model to examine the factors that affect users' intention to disclose their privacy on social media platforms. Drawing on the cognition-affect-conation model and multidimensional development theory, the model integrates multidimensional factors of platform features, group effects, trust and privacy concern to complement existing theoretical frameworks and privacy disclosure literature. By understanding the complex dynamics behind privacy disclosure, this study helps platform providers and policymakers develop effective strategies to ensure the vitality and momentum of the social media ecosystem.
Yang H.(., Chan T.K., Tran H., Nguyen B., Lin H.
2024-05-17 citations by CoLab: 0 Abstract  
PurposeThis research examines how universities enhance the virality of their social media messages among students. Specifically, we explore whether and how positive affective content in universities’ social media posts can influence sharing behavior. We also investigate the mediating roles of perceived effort and positive emotional reaction, as well as the moderating effect of visual content (i.e. photos).Design/methodology/approachDrawing upon the emotions as social information model, we conducted (1) an online experiment (N = 222) and (2) text analysis of 1,269,798 Twitter posts extracted from the accounts of 94 UK universities over 11 years (2010–2020) to test our hypotheses.FindingsThe findings show that social media posts containing positive affective content encourage sharing behavior and the relationship is mediated by both perceived effort and positive emotional reaction. An additional finding suggests that the use of visual content (photos) strengthens the relationship between positive affective content and sharing behaviors through an interaction effect.Originality/valueThis study contributes to the scant research focusing on positive affective content in the higher education context. The findings shed light on how universities could create social media communications that engage current and prospective students.
Zhang Z., Zhang Z., Liu S., Zhang Z.
2024-05-01 citations by CoLab: 3 Abstract  
Nearly all ecommerce platforms have adopted hierarchical status systems to encourage user contributions. Although many studies have explored how online reviewer status influences consumer contributions, how reviewer status affects reviewer preferences for anonymity, which is an important factor in consumer assessments of review credibility and consumer purchase decisions, is still unclear. In this paper, underpinned by hierarchical status and psychological theories, an empirical analysis is conducted regarding the ways that reviewer status shapes reviewer preferences for anonymity. Utilizing online review data from Ctrip.com and employing advanced text mining methods, we reveal that reviewer status positively influences their preferences for anonymity, but this effect is weaker for business-travel reviewers than for leisure-travel reviewers. Additionally, this positive effect is attenuated by reviewer openness but strengthened by reviewer conscientiousness. However, the moderating effect of reviewer neuroticism is not significant. Our findings substantially contribute to the literature on hierarchical status and information disclosure and provide significant practical guidance for incentive designers in the ecommerce domain.
Fang M., Wang Y., Yang L., Wu H., Yin Z., Liu X., Xie Z., Kong Z.
Electronics (Switzerland) scimago Q2 wos Q2 Open Access
2024-04-29 citations by CoLab: 0 PDF Abstract  
Web3.0, as the link between the physical and digital domains, faces increasing security threats due to its inherent complexity and openness. Traditional intrusion detection systems (IDSs) encounter formidable challenges in grappling with the multidimensional and nonlinear traffic data characteristic of the Web3.0 environment. Such challenges include insufficient samples of attack data, inadequate feature extraction, and resultant inaccuracies in model classification. Moreover, the scarcity of certain traffic data available for analysis by IDSs impedes the system’s capacity to document instances of malicious behavior. In response to these exigencies, this paper presents a novel approach to Web3.0 intrusion detection, predicated on the utilization of cycle-consistent generative adversarial networks (CycleGANs). Leveraging the data transformation capabilities of its generator, this method facilitates bidirectional conversion between normal Web3.0 behavioral data and potentially intrusive behavioral data. This transformative process not only augments the diversity and volume of recorded intrusive behaviors but also clandestinely simulates various attack scenarios. Furthermore, through fostering mutual competition and learning between the discriminator and generator, the approach enhances the ability to discern the defining characteristics of potential intrusive behaviors, thereby bolstering the accuracy of intrusion detection. To substantiate the efficacy of the CycleGAN-based intrusion detection method, simulation experiments were conducted utilizing public datasets, including KDD CUP 1999 (KDD), CIC-DDOS2019, CIC-IDS2018, and SR-BH 2020. The experimental findings evince the method’s remarkable accuracies across the four datasets, attaining rates of 99.81%, 97.79%, 89.25%, and 95.15%, respectively, while concurrently maintaining low false-positive rates. This research contributes novel insights and methodologies toward the advancement of Web3.0 intrusion detection through the application of CycleGAN technology, which is poised to play a pivotal role in fortifying the security landscape of Web3.0.
Fan S., Yao S., Wu D.
Library Hi Tech scimago Q1
2024-04-12 citations by CoLab: 1 Abstract  
PurposeCulture is considered a critical aspect of social media usage. The purpose of this paper is to explore how cultures and languages influence multilingual users' cross-cultural information sharing patterns.Design/methodology/approachThis study used a crowdsourcing survey with Amazon Mechanical Turk to collect qualitative and quantitative data from 355 multilingual users who utilize two or more languages daily. A mixed-method approach combined statistical, and cluster analysis with thematic analysis was employed to analyze information sharing patterns among multilingual users in the Chinese cultural context.FindingsIt was found that most multilingual users surveyed preferred to share in their first and second language mainly because that is what others around them speak or use. Multilingual users have more diverse sharing characteristics and are more actively engaged in social media. The results also provide insights into what incentives make multilingual users engage in social media to share information related to Chinese culture with the MOA model. Finally, the ten motivation factors include learning, entertainment, empathy, personal gain, social engagement, altruism, self-expression, information, trust and sharing culture. One opportunity factor is identified, which is convenience. Three ability factors are recognized consist of self-efficacy, habit and personality.Originality/valueThe findings are conducive to promoting the active participation of multilingual users in online communities, increasing global resource sharing and information flow and promoting the consumption of digital cultural content.
Bae H., Cha K.
2024-04-09 citations by CoLab: 0 Abstract  
Abstract The advancement of internet technology has facilitated the emergence of relational Social Network Services (SNS), offering services based on individuals' social connections. SNS users utilize personal information as a means of self-expression, thereby constructing their own social networks. However, the proliferation of personal information breaches has emerged as a significant contemporary concern due to the escalating use of SNS platforms. Recent incidents predominantly involve the collection and dissemination of information voluntarily disclosed on SNS, rather than by hacking. Despite the imperative need to forestall such breaches, there is a dearth of empirically applicable methodologies to gauge the risk of personal information leakage. Prior research methodologies for quantitatively assessing breach risk have predominantly concentrated on evaluating personal profiles alone, with limited consideration given to the potential identifiability of personal information embedded within uploaded content. Furthermore, these studies have often relied on surveys to ascertain users' perceptions of personal information leakage risk, hereby constraining their practical applicability and difficult to fulfill the objective of preventing personal information breaches. Hence, this study proposes a method for estimating privacy leakage risk based on the privacy-dilemma framework, which underscores the dilemmas SNS users encounter in managing both personal profiles and content data. Leveraging Social Network Analysis (SNA) to capture the nuances of relational SNS characteristics, we aim to enhance methodologies proposed in previous studies. The Multiple Regression Quadratic Assignment Procedure (MR-QAP) analysis is employed to delineate the factors influencing the risk score. This methodological approach holds promise in furnishing practical insights into privacy protection.

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