scholarly journals CEPTM: A Cross-Edge Model for Diverse Personalization Service and Topic Migration in MEC

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Hongchen Wu ◽  
Huaxiang Zhang ◽  
Lizhen Cui ◽  
Xinjun Wang
Keyword(s):  
Information Disclosure ◽  
Management Strategies ◽  
Mobile User ◽  
High Rate ◽  
Privacy Concern ◽  
Self Disclosure ◽  
Privacy Concerns ◽  
Individual Privacy ◽  
Computing Paradigm ◽  
User Data

For several reasons, the cloud computing paradigm, e.g., mobile edge computing (MEC), is suffering from the problem of privacy issues. MEC servers provide personalization services to mobile users for better QoE qualities, but the ongoing migrated data from the source edge server to the destination edge server cause users to have privacy concerns and unwillingness of self-disclosure, which further leads to a sparsity problem. As a result, personalization services ignore valuable user profiles across edges where users have accounts in and tend to predict users’ potential purchases with insufficient sources, thereby limiting further improvement of QoE through personalization of the contents. This paper proposes a novel model, called CEPTM, which (1) collects mobile user data across multiple MEC edge servers, (2) improves the users’ experience in personalization services by loading collected diverse data, and (3) lowers their privacy concern with the improved personalization. This model also reveals that famous topics in one edge server can migrate into several other edge servers with users’ favorite content tags and that the diverse types of items could increase the possibility of users accepting the personalization service. In the experiment section, we use exploratory factor analysis to mathematically evaluate the correlations among those factors that influence users’ information disclosure in the MEC network, and the results indicate that CEPTM (1) achieves a high rate of personalization acceptance due to the availability of more data as input and highly diverse personalization as output and (2) gains the users’ trust because it collects user data while respecting individual privacy concerns and providing better personalization. It outperforms a traditional personalization service that runs on a single-edge server. This paper provides new insights into MEC diverse personalization services and privacy problems, and researchers and personalization providers can apply this model to merge popular users’ like trends throughout the MEC edge servers and generate better data management strategies.

Privacy Concern of Health Information Disclosure in mHealth: The Moderate Effect of Social Support (Preprint)

2020 ◽  
Author(s):  
Yuanyuan Dang ◽  
Shanshan Guo ◽  
Xitong Guo
Keyword(s):  
Social Support ◽  
Health Information ◽  
Emotional Support ◽  
Information Disclosure ◽  
Perceived Health ◽  
Privacy Concern ◽  
Informational Support ◽  
Privacy Concerns ◽  
Information Sensitivity ◽  
Moderate Effect

BACKGROUND The mobile health (mHealth) provides a new opportunity for patients’ disease prediction and health self-management. At the same time, privacy problems in mHealth have brought forth significant attention concerning patients' online health information disclosure and hindered mHealth development. OBJECTIVE Privacy calculus theory (PCT) has been widely used to understand personal information disclosure behaviors with the basic assumption of a national and linear decision-making process. However, people’s cognitive behavior processes are complex and mutual. In attempting to close this knowledge gap, we further optimize the information disclosure model of patients based on PCT by identifying the mutual relationship between costs (privacy concerns) and benefits. Social support, which has been proved to be a distinct and significant disclosure benefit of mHealth, was chosen to be the representative benefit of information disclosure in mHealth. METHODS From an individual perspective, a structural equation model with privacy concerns, health information disclosure intention in mHealth, and social support from mHealth has been examined. RESULTS 253 randomly selected participants provided validated questionnaire. The result indicated that perceived health information sensitivity positively enhances the privacy concern (0.505, p<0.01), and higher privacy concern levels will decrease the health information disclosure intention (-0.338, p<0.01). Various aspects of individual characters influence perceived health information sensitivity in different ways. The informational support has a negatively moderate on reduce the positive effect between perceived health information sensitivity and privacy concerns (-0.171, p<0.1) and will decrease the negative effect between privacy concerns and health information disclosure intention(-0.105, p<0.1). However, emotional support has no directly moderate effect on both privacy concerns and health information disclosure intention. CONCLUSIONS The results indicate that social support can be regarded as a disutility reducer, that is, on the one hand, it reduces the privacy concerns of patients; on the other hand, it also reduces the negative impact of privacy concerns on information disclosure intention. Moreover, the moderate effect of social support is partially supported. Informational support, one demission of social support, is significant, while the other demission, emotional support, is not significant in mHealth. Furthermore, the results are different among patients with different individual characteristics. This study also provides specific theoretical and practical implications to enhance the development of mHealth.

An examination of the information disclosure behavior of infertility bloggers

2014 ◽  
Vol 66 (2) ◽  
pp. 175-201 ◽  
Author(s):  
Maria Knoll ◽  
Jenny Bronstein
Keyword(s):  
Information Disclosure ◽  
Design Methodology ◽  
The Other ◽  
High Rate ◽  
Sensitive Information ◽  
Self Disclosure ◽  
Content Type ◽  
Alternate Explanation ◽  
Infertility Treatments ◽  
Disclosure Patterns

Purpose – The study aimed to investigate the information disclosure behavior of women bloggers who suffer from infertility by examining their self-disclosure as it relates to the anonymity patterns they adopted. Design/methodology/approach – A survey was distributed to approximately 300 authors of infertility blogs, 135 bloggers answered the request to take part in the study. The survey gathered basic demographic and blogging practice data, and measured different elements of the bloggers' discursive and visual anonymity as well as their patters of self-disclosure. Findings – Findings reveal that the majority of respondents identify themselves on their blogs and only a small percentage decided to be totally anonymous, and about half of the bloggers post actual photos of themselves and their lives. The participants reported a high rate of self-disclosure, revealing sensitive information, letting their defenses down, disclosing highly intimate details about their lives, writing openly about their infertility treatments on their blog. No significant correlation was observed between visual and discursive anonymity and the perceived self-disclosure of participants. Results show that the more anonymous the bloggers are, the more afraid they become that their blog may be read by people they know offline. On the other hand, the more identifiable the bloggers are, the more willingness they show to share the content of their journal with people they know offline. The majority of participants expressed concerns that blogging could negatively impact their lives. Originality/value – This study explores an alternate explanation through the examination of the bloggers' self-disclosure patterns as they relate to the degree of anonymity adopted.

scholarly journals Investigating Privacy and Information Disclosure Behavior in Social Electronic Commerce

2019 ◽  
Vol 11 (12) ◽  
pp. 3311 ◽  
Author(s):  
Yuan Sun ◽  
Shuyue Fang ◽  
Yujong Hwang
Keyword(s):  
Information Disclosure ◽  
Current Trend ◽  
Perceived Benefits ◽  
Privacy Concern ◽  
Privacy Concerns ◽  
Group Buying ◽  
Internet Users ◽  
Privacy Calculus ◽  
Negative Impacts ◽  
A Current

Social e-commerce has steadily emerged as a current trend for an enormous amount of Internet users. Despite the popularity and prevalence of social e-commerce, many users hesitate to disclose their information due to privacy concerns. This resistance from users impedes the development of social e-commerce enterprises. In order to help enterprises collect more user information and establish better development strategies, this research builds on the Privacy Antecedent-Privacy Concern-Outcomes (APCO) model and the theory of privacy calculus. This research investigates how the privacy antecedents of hot topic interactivity and group buying experience influence users’ privacy concerns and perceived benefits as well as how to further influence users’ information disclosure behavior. The results from 406 questionnaire responses indicate that hot topic interactivity and group buying experience have significant negative impacts on privacy concerns and significant positive impacts on perceived benefits. Privacy concerns negatively influence the behavior of information disclosure while perceived benefits positively influence the behavior of information disclosure. Based on these results, social e-commerce enterprises should promote users’ behaviors of hot topic interactivity and group buying to stimulate users’ information disclosure behavior.

scholarly journals Do privacy concerns determine online information disclosure? The case of internet addiction

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nik Thompson ◽  
Atif Ahmad ◽  
Sean Maynard
Keyword(s):  
Internet Addiction ◽  
Information Disclosure ◽  
Structural Equation ◽  
Cost Benefit ◽  
Online Information ◽  
Self Disclosure ◽  
Content Type ◽  
Privacy Concerns ◽  
Privacy Calculus ◽  
The Impact

Purpose It is a widely held belief that users make a rational cost-benefit decision when choosing whether to disclose information online. Yet, in the privacy context, the evidence is far from conclusive suggesting that strong and as-yet unmeasured influences on behaviour may exist. This paper aims to demonstrate one such link – the effect of internet addiction on information disclosure. Design/methodology/approach Data from 216 Web users was collected regarding their perceptions on privacy and information disclosure intentions as well as avoidance behaviour, an element of internet addiction. Using a research model based on the Privacy Calculus theory, structural equation modelling was applied to quantify the determinants of online disclosure under various conditions. Findings The authors show that not all aspects of privacy (a multi-dimensional construct) influence information disclosure. While concerns about data collection influence self-disclosure behaviour, the level of awareness about privacy does not. They next examine the impact of internet addiction on these relationships, finding that internet addiction weakens the influence of privacy concerns to the point of non-significance. Originality/value The authors highlight some of the influences of self-disclosure behaviour, showing that some but not all aspects of privacy are influential. They also demonstrate that there are powerful influences on user behaviour that have not been accounted for in prior work; internet addiction is one of these factors. This provides some of the first evidence of the potentially deleterious effect of internet addiction on the privacy calculus.

Conceptual Paper: Sentience of Big Data towards User Privacy Concerns and Online Self-Disclosure Activities

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
A Ismail ◽  
◽  
M R Hamzah ◽  
H Hussin ◽  
◽  
...  
Keyword(s):  
Big Data ◽  
Personal Data ◽  
User Privacy ◽  
Self Disclosure ◽  
Privacy Concerns ◽  
Perceived Risks ◽  
User Data ◽  
Conceptual Paper ◽  
Privacy Breaches ◽  
Different Sources

Big data allows widespread use and exchange of user data, and this will lead to the possibility of privacy breaches. Governments and corporations will incorporate personal data from different sources and learn a great deal about people and in turn, raise concerns about privacy. This paper will provide a conceptual understanding on the antecedents towards user privacy concerns and online self-disclosure activities, which are the knowledge and perceived risks of big data. In this paper, big data knowledge is hypothesized to decrease privacy concerns, meanwhile perceived risks is suggested to increase the outcome. Based on the framework, propositions are formulated as a basis for the study that will follow.

Prior Negative Experience, Online Privacy Concerns and Intent to Disclose Personal Information in Chinese Social Media

2014 ◽  
Vol 10 (2) ◽  
pp. 23-44
Author(s):  
Hongwei “Chris” Yang
Keyword(s):  
Social Media ◽  
Perceived Risk ◽  
Information Disclosure ◽  
Personal Information ◽  
Online Privacy ◽  
Online Information ◽  
Sensitive Information ◽  
Negative Experience ◽  
Self Disclosure ◽  
Privacy Concerns

A paper survey of 489 Chinese college students was conducted in spring, 2012 to test a conceptual model of online information disclosure in social media. It shows that young Chinese SNS users' prior negative experience of online disclosure significantly increased their online privacy concerns and their perceived risk. Their online privacy concerns undermined their trust of online companies, marketers and laws to protect privacy and elevated their perceived risk. Their trust strongly predicted their intent to disclose the lifestyle and sensitive information. Their online privacy concerns only inhibited them from disclosing sensitive information in social media. However, their prior negative experience did not directly predict their intent of self-disclosure on SNS. Implications for academia and industry are discussed.

The willingness to disclose personal information

2019 ◽  
Vol 28 (2) ◽  
pp. 161-181 ◽  
Author(s):  
Ibrahim M. Al-Jabri ◽  
Mustafa I. Eid ◽  
Amer Abed
Keyword(s):  
Saudi Arabia ◽  
Information Disclosure ◽  
Personal Information ◽  
Negative Relationship ◽  
Extensive Literature ◽  
Privacy Concern ◽  
Content Type ◽  
Privacy Concerns ◽  
Positive Effects ◽  
Willingness To Disclose

Purpose Customer privacy and security are major concerns. Online firms worldwide collect customer data for various reasons. This study aims to investigate factors that motivate and hinder a customer’s willingness to disclose personal information (WTD) to online firms on e-commerce websites. Design/methodology/approach Based on an extensive literature review, three sets of factors have been identified. These sets of factors are privacy concern, perceived disclosure benefits and privacy assurances. It is hypothesized that privacy concerns negatively affect the disclosure of personal information, while the perceived benefits of disclosure have positive effects. Privacy assurances would positively affect information disclosure and attenuate the negative effect of privacy concerns on the disclosure of personal information. The authors gathered data from 253 online customers in Saudi Arabia. Findings The results indicate that perceived disclosure benefits and privacy concerns have a significant positive and negative relationship, respectively, with WTD online. Privacy assurances had neither a direct nor a moderating effect on information disclosure. Research limitations/implications The findings will inform online firms about the factors that prevent or motivate customers to disclose personal information. Originality/value The effect of privacy concerns and benefits on personal information disclosure are not fully understood in Saudi Arabia. This study reveals more insights into the specific factors that make online customers reluctant or motivated to disclose their personal information.

scholarly journals Health Privacy Information Self-Disclosure in Online Health Community

2021 ◽  
Vol 8 ◽  
Author(s):  
Wang Yuchao ◽  
Zhou Ying ◽  
Zangyi Liao
Keyword(s):  
Factor Analysis ◽  
Structural Equation ◽  
Fundamental Problem ◽  
Practical Significance ◽  
Privacy Concern ◽  
Self Disclosure ◽  
Privacy Concerns ◽  
Online Health Community ◽  
Personalized Services ◽  
Health Community

The scarcity of medical resources is a fundamental problem worldwide; the development of information technology and the Internet has given birth to online health care, which has alleviated the above problem. The survival and sustainable development of the online health community requires users to continuously disclose their health and privacy. Therefore, it is a great practical significance to find out the factors and mechanisms that promote users' self-disclosure in the online health community. From the perspective of individual and situation interaction, this study constructed influencing factors model of health privacy information self-disclosure. Finally, we collected 264 valid samples from the online health community through online and offline questionnaire surveys and then use the SPSS20.0 and AMOS21.0 to conduct exploratory factor analysis, confirmatory factor analysis, scale reliability and validity analysis, and structural equation model analysis. The main findings are as follows: trust in websites and trust in doctors reduce the privacy concern. The privacy trade-off will not occur when trust is enough to offset the privacy concerns caused by personalized services, reciprocity norms, and other factors. Second, reciprocity norms are inevitably compulsive, which will increase privacy concerns. However, based on voluntariness, reciprocity norms can enhance user trust. Third, service quality caused by personalized services not only enhance the social rewards of users but also eliminate the privacy concern. Fourth, users' health privacy attention and information sensitivity are too high to decrease the influence of user' privacy concerns on personal health privacy information disclosure. The conclusions of this paper will help us to supplement privacy calculus theory and the application scope of the attention-based view. The proposed strategy of this article can be used to stimulate the information contribution behavior of users and improve the medical service capabilities in online health community.

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