Level Of Privacy Concern Research Articles

Federated Learning Using Multi-Modal Sensors with Heterogeneous Privacy Sensitivity Levels

Data from multi-modal sensors, such as RGB cameras, thermal cameras, microphones, and mmWave radars, have gradually been adopted in various classification problems for better accuracy. Some sensors, like RGB cameras and microphones, however, capture privacy-invasive data, which are less likely to be used in centralized learning. Although the Federated Learning (FL) paradigm frees clients from sharing their sensor data, doing so results in reduced classification accuracy and increased training time. In this article, we introduce a novel Heterogeneous Privacy Federated Learning (HPFL) paradigm to better capitalize on the less privacy-invasive sensor data, such as thermal images and mmWave point clouds, by uploading them to the server for closing the performance gap between FL and centralized learning. HPFL not only allows clients to keep the more privacy-invasive sensor data private, such as RGB images and human voices, but also gives each client total freedom to define the levels of their privacy concern on individual sensor modalities. For example, more sensitive users may prefer to keep their thermal images private, while others do not mind sharing these images. We carry out extensive experiments to evaluate the HPFL paradigm using two representative classification problems: semantic segmentation and emotion recognition. Several key findings demonstrate the merits of HPFL: (i) compared to FedAvg, it improves foreground accuracy by 18.20% in semantic segmentation and boosts the F1-score by 4.20% in emotion recognition, (ii) with heterogeneous privacy concern levels, it achieves an even larger F1-score improvement of 6.17–16.05% in emotion recognition, and (iii) it also outperforms the state-of-the-art FL approaches by 12.04–17.70% in foreground accuracy and 2.54–4.10% in F1-score.

Research on Privacy Disclosure Behavior of Mobile App Users from Perspectives of Online Social Support and Gender Differences

The provision of information and emotions is the core competitive edge for mobile apps to attract users to utilize their services and functionalities. Considering user demands and gender differences, it holds great significance for mobile apps to optimize personalized services by elucidating the formation mechanism of privacy disclosure behavior from the perspective of online social support (information and emotional). We adopt online social support theory and construct a model based on Stimulus-Organism-Response (SOR) framework to collect questionnaire data from 548 respondents for empirical analysis. The results showed that both online information support and online emotional support have direct or indirect positive effects on privacy disclosure behavior, with perceived justice and privacy concern mediating this effect. Perceived justice has a negative impact on privacy concern. Besides, females exhibit higher levels of privacy concern and lower levels of disclosure, and there are differences in the types of demand support between males and females in privacy decision-making.

Standardization and evaluation of indicators for quantifying antimicrobial use on U.S. dairy farms

Antimicrobial resistance (AMR) is a global One Health threat. A portion of AMR development can be attributed to antimicrobial use (AMU) in animals, including dairy cattle. Quantifying AMU on U.S. dairy farms is necessary to inform antimicrobial stewardship strategies and help evaluate the relationship between AMU and AMR. Many AMU indicators have been proposed for quantifying AMU in dairy cattle. However, these indicators are difficult to interpret and compare because they differ in the type of data used, the calculation approach, and the definitions of variables and parameters used in the calculation. Therefore, we selected 16 indicators (count-based, mass-based, and dose-based) applicable for quantifying AMU on U.S. dairy farms. We systematized the indicators by standardizing their variables and parameters to improve their interchangeability, interpretation, and comparability. We scored indicators against six data-driven criteria (assessing their accuracy, data and effort needs, and level of privacy concern) and five stewardship-driven criteria (assessing their ability to capture trends and inform antimicrobial stewardship). The derived standardized indicators will aid farmers and veterinarians in selecting suitable indicators based on data availability and stewardship needs on a farm. The comparison of indicators revealed a trade-off requiring farmers to balance the granularity of data necessary for an accurate indicator and effort to collect the data, and a trade-off relevant to farmers interested in data sharing to inform stewardship because more accurate indicators are typically based on more sensitive information. Indicators with better accuracy tended to score better in stewardship criteria. Overall, two dose-based indicators, estimating the number of treatments and administered doses, scored best in accuracy and stewardship. Conversely, two count-based indicators, estimating the length of AMU, and a mass-based indicator, estimating the mass of administered antimicrobials, performed best in the effort and privacy criteria. These findings are expected to benefit One Health by aiding the uptake of farm-level AMU indicators by U.S. dairy farms.

“All apps do this”: Comparing Privacy Concerns Towards Privacy Tools and Non-Privacy Tools for Social Media Content

Users report that they have regretted accidentally sharing personal information on social media. There have been proposals to help protect the privacy of these users, by providing tools which analyze text or images and detect personal information or privacy disclosure with the objective to alert the user of a privacy risk and transform the content. However, these proposals rely on having access to users’ data and users have reported that they have privacy concerns about the tools themselves. In this study, we investigate whether these privacy concerns are unique to privacy tools or whether they are comparable to privacy concerns about non-privacy tools that also process personal information. We conduct a user experiment to compare the level of privacy concern towards privacy tools and nonprivacy tools for text and image content, qualitatively analyze the reason for those privacy concerns, and evaluate which assurances are perceived to reduce that concern. The results show privacy tools are at a disadvantage: participants have a higher level of privacy concern about being surveilled by the privacy tools, and the same level concern about intrusion and secondary use of their personal information compared to non-privacy tools. In addition, the reasons for these concerns and assurances that are perceived to reduce privacy concern are also similar. We discuss what these results mean for the development of privacy tools that process user content.

Investigation of the Relationship between Online Privacy Concerns and Internet Addiction among University Students

The fact that the cyber environment does not have clear boundaries, and the difficulties in taking control of this environment, can turn online sharing into a source of concern in terms of privacy. In particular, the tendency of internet addicts to use the internet uncontrollably can increase the probability of experiencing privacy concerns. This research aims to reveal the relationship between internet addiction levels and online privacy concerns of university youth, one of the segments most addressed by web-based communication technologies. The research was designed with a cross-sectional and correlational survey design within the scope of quantitative research methods. The sample of the research consists of 524 students studying at a state university in Turkey. Quantitative data were collected face-to-face through an introductory information form, and a questionnaire including the scales of “Online Privacy Concern” and “Internet Addiction”. The study determined that online privacy concerns were significantly higher among first-year students, female students, and those using Instagram accounts. It was determined that male students had higher internet addiction levels. In the study, it was revealed that as the internet addiction levels of university students increased, their online privacy concerns also increased. In addition, it was determined that internet addiction explained 15.7% of the total variance of online privacy concerns. Based on the positive relationship between internet addiction and online privacy concern levels of university students, it can be said that the problems related to internet use intersect, intertwine and feed each other.

Privacy Concerns for Visual Assistance Technologies

People who are blind share their images and videos with companies that provide visual assistance technologies (VATs) to gain access to information about their surroundings. A challenge is that people who are blind cannot independently validate the content of the images and videos before they share them, and their visual data commonly contains private content. We examine privacy concerns for blind people who share personal visual data with VAT companies that provide descriptions authored by humans or artifcial intelligence (AI) . We frst interviewed 18 people who are blind about their perceptions of privacy when using both types of VATs. Then we asked the participants to rate 21 types of image content according to their level of privacy concern if the information was shared knowingly versus unknowingly with human- or AI-powered VATs. Finally, we analyzed what information VAT companies communicate to users about their collection and processing of users’ personal visual data through their privacy policies. Our fndings have implications for the development of VATs that safeguard blind users’ visual privacy, and our methods may be useful for other camera-based technology companies and their users.

Branding through visitors: how cultural differences affect brand co-creation in independent hotels in Iran

PurposeIn most countries, independent hotels are a major contributor to both national economy and the hospitality sector, but to the best of the authors’ knowledge, there is a lack of any study on brand co-creation (BCC) in independent hotels. This study aims to examine the interrelationship of moral judgement (MJ), self–brand connection, customer–brand engagement (CBE), electronic word-of-mouth (eWOM) and how BCC occurs in independent hotels and contrasts visitors’ perspectives between two different Global Leadership and Organizational Behavior Effectiveness clusters in independent hotels. Furthermore, this study also examines the moderating impact of privacy concern (PC) on the relationship between eWOM and brand co-creation.Design/methodology/approachData were collected from two groups of tourists, Iranian (290) and European (224), who visited and stayed in independent hotels in some major cities in Iran. The structural equation modelling using AMOS 22 was adopted to test the hypotheses.FindingsThe study’s findings revealed that there are significant differences between two culturally different travellers in terms of selected variables, suggesting that MJ is a main antecedent of CBE, which leads to eWOM among Iranian travellers, which consequently leads to BCC. Moreover, the study’s data indicates that European travellers show a high level of PCs while staying in independent hotels in Iran, which prevents them from sharing and getting engaged in the social media, which could delay the BCC process especially in international level.Originality/valueThis study contributes to literature by providing new insights on the differences in the concept of brand co-creation between two culturally different groups in the context of independent hotels, which require special attention of independent hotel managers.

Privacy Concerns About Health Information Disclosure in Mobile Health: Questionnaire Study Investigating the Moderation Effect of Social Support.

BackgroundMobile health (mHealth) provides a new opportunity for disease prediction and patient health self-management. However, privacy problems in mHealth have drawn significant attention to patients’ online health information disclosure and to the possibility that privacy concerns may hinder mHealth development.ObjectivePrivacy calculus theory (PCT) has been widely used to understand personal information disclosure behaviors with the basic assumption of a rational and linear decision-making process. However, cognitive behavior processes are complex and mutual. In an attempt to gain a fuller understanding of information disclosure behavior, we further optimize a PCT-based information disclosure model by identifying the mutual relationship between costs (privacy concerns) and benefits. Social support, which has been proven to be a distinct and significant disclosure benefit of mHealth, was chosen as the representative benefit of information disclosure.MethodsWe examine a structural equation model that incorporates privacy concerns, health information disclosure intention in mHealth, and social support from mHealth, all at the individual level.ResultsA validated questionnaire was completed by 253 randomly selected participants. The result indicated that perceived health information sensitivity positively enhances patients’ privacy concern (beta path coefficient 0.505, P<.001), and higher privacy concern levels will decrease their health information disclosure intention (beta path coefficient –0.338, P<.001). Various individual characteristics influence perceived health information sensitivity in different ways. One dimension of social support, informational support, negatively moderates the effect of the relationship between perceived health information sensitivity and privacy concerns (beta path coefficient –0.171, P=.092) and the effect of the relationship between privacy concerns and health information disclosure intention (beta path coefficient –0.105, P=.092). However, another dimension, emotional support, has no direct moderation effect on the relationship between privacy concerns and health information disclosure intention.ConclusionsThe results indicate that social support can be regarded as a disutility reducer. That is, on the one hand, it reduces patients’ privacy concerns; on the other hand, it also reduces the negative impact of privacy concerns on information disclosure intention. Moreover, the moderation effect of social support is partially supported. Informational support, one dimension of social support, is significant (beta path coefficient –0.171, P=.092), while the other dimension, emotional support, is not significant (beta path coefficient –0.137, P=.146), 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.

Twitter Privacy Concern: The Effect of Twitter Profile

Privacy concern vary from one to another. Sensitive information related to finance and health are most of the concern. The vast spread of using social media/ micro-blogging platforms, i.e. Twitter, as a desirable channel of online communication, has changed the peoples' understanding of what is private communication and whether they should or should not be concerned about their privacy. This paper examines the relationship between the level of privacy concern of Twitter users and their gender, experience on Twitter, type of their Twitter account and type of their username. A survey in the form of a questionnaire has been conducted in Saudi Arabia. The research compares privacy concern from the perspective of male and female, old and new Twitter users, private and public account holders and nickname and real name username holders. Determining the Chi square and using T-test and ANOVA, this research shows that the individual’s privacy concerns are affected by the Twitter users’ profile; gender, number of the years on Twitter, the type of Twitter account and username.

MAKING SENSE OF SOCIAL MEDIA PRIVACY: A FRAMING EXPERIMENT

As individuals trade information to access social media products and services, privacy has become increasingly valuable. Elite discourses have tended to frame privacy in terms of its vertical or institutional dimensions, but much less attention has been given to how users individually interpret and make sense of this complex notion. How do privacy sense-making processes intersect with privacy concerns and self-efficacy? What happens to these outcomes when an individual’s ideas about privacy collide with framing by an authoritative source? This project poses a 2x2 survey-based experiment with 628 subjects to explore these questions. We examine differences in privacy concerns and self-efficacy resulting from an individual’s own conceptualization of privacy, as well as from the presentation of similar and alternative framing of the concept. Preliminary results indicate that while individual conceptualizations show no differences in outcomes, higher levels of privacy self-efficacy result from the framing of privacy in horizontal terms and lower levels of privacy concern result when framing is consistent with the individual’s conceptualization. Strategic and practical implications of these findings are discussed.

Personalized advertisements with integration of names and photographs: An eye-tracking experiment

This article examines the influence of a job recruitment advertisement personalized with a recipient's name and photograph on the visual attention to the advertisement, the attitudes toward the advertisement and, ultimately, job-pursuit intentions. Perceived ad intrusiveness and attitudinal persuasion knowledge may function as parallel mediators of visual attention and attitude toward the advertisement, with personal privacy concerns as a moderator of this relationship. In a between-subjects eye-tracking experiment, 72 participants view an advertisement on LinkedIn that is either personalized or not personalized. Although the participants fixate on the personalized advertisement more frequently and view it longer, they do not notice it faster or return to it more frequently. Furthermore, enhanced visual attention augments perceived intrusiveness, regardless of participants' levels of privacy concern, and decreases attitudinal persuasion knowledge for those who are less concerned about privacy.

Self-censorship in social networking sites (SNSs) – privacy concerns, privacy awareness, perceived vulnerability and information management

PurposeThis paper aims to investigate behavioural changes related to self-censorship (SC) in social networking sites (SNSs) as new methods of online surveillance are introduced. In particular, it examines the relationships between SC and four related factors: privacy concerns (PC), privacy awareness (PA), perceived vulnerability (PV) and information management (IM).Design/methodology/approachA national wide survey was conducted in the UK (N = 519). The data were analysed to present both descriptive and inferential statistical findings.FindingsThe level of online SC increases as the level of privacy concern increases. The level of privacy concern increases as the levels of PA and PV increase and the level of effective IM decreases.Originality/valueThis study extends the literature on online SC, showing that PCs increase the level of SC in SNSs. It provides support for three antecedent factors to PC which impact upon levels of SC when communicating in SNSs.

The effect of personality traits on online privacy concern

his paper examines personality traits as antecedents of online privacy concern. The aim of the research is to analyze if and how personal characteristics of Internet users affect their concern for privacy in online environment. The theoretical framework consisting of the Big Five theory of personality traits has been used to test the variations in online privacy concern. The model includes a range of other variables that might affect online privacy concern, such as sociodemographic factors, cultural values and computer literacy. The empirical analysis is based on survey data collected in 2016 on a large sample of 2,060 Internet users in Croatia. Results of bothOLS and ordered probit estimations show that two personality traits dimensions, namely extraversion and neuroticism, signifi cantly determine the level of online privacy concern. The more extraverted, i.e., more energetic and outgoing Internet user is less concerned about his/her online privacy, whilst the more neurotic one is more concerned. Privacy awareness, computer anxiety and previous negative experience were also observed as antecedents, all positively affecting the level of privacy concern of Internet users. The results of this research fi ll the gap in the underexplored area of personality traits and onlineprivacy concern literature and contribute to developing an extended model of online privacy concern.

Impact of Privacy Concern on Using Mobile Social Networking Apps: An Empirical Study

In this study, we investigated the level of privacy concern among users of mobile social networking (MSN) apps, and the effect of users' privacy concern on their acceptance of MSN apps. Based on the social exchange theory as well as the uses and gratification theory, we developed a research model to hypothesise the relationships among privacy-related constructs. We tested the research model using the data collected from a survey study. Our data analysis indicates that survey respondents have privacy concern when using MSN apps. However, the direct effect of privacy concern on user's behavioural intention is not statistically significant, while enjoyment has a significant positive influence on the behavioural intention. The antecedents of enjoyment and privacy concern are found to significantly affect their respective dependent variable. The findings help researchers and practitioners better understand the impact of privacy concern on users' acceptance of MSN apps.

A power-responsibility equilibrium framework for fairness: Understanding consumers' implicit privacy concerns for location-based services

Location-based services rely on geospatial technologies that involve data that offer information of a prosocial nature – such as a nearby highway closure. The objective of this mixed method research is to examine consumers' concerns about privacy and fairness that pertain to these services. The basis for this research is the theory on the power-responsibility equilibrium. Study 1 qualitatively examines 332 comments; Study 2 uses a quantitative structural equation model with a sample of 291 non-students. Our findings indicate that fairness perceptions of privacy-related policies are enhanced when a consumer has a higher internal locus of control, higher attitude toward the communication, and lower level of privacy concern.

A multicultural study of biometric privacy concerns in a fire ground accountability crisis response system

Biometric technology is rapidly gaining popularity as an access control mechanism in the workplace. In some instances, systems relying on biometric technology for access control have not been well received by employees. One potential reason for resistance may be perceived privacy issues associated with organizational collection and use of biometric data. This research draws on previous organizational information handling and procedural fairness literature to frame and examine these underlying privacy issues. Perceived accountability, perceived vulnerability, and distrust were distilled from the previous literature as the primary dimensions of employee privacy concerns related to biometric technology. This study assesses the effects of these privacy concerns, how they vary based on the cultural influences of Anglos and Hispanics.Fire ground accountability is a critical management objective in the firefighting domain. In multi-unit or multi-agency crisis response scenarios, the on-scene incident commander tracks and accounts for each first responder. This research designed and deployed a new fire ground accountability system that tracked firefighters through finger pattern-based biometric logins to their assigned positions on the firefighting apparatus. An instrument measuring level of privacy concern on three underlying dimensions and demographic data was developed, validated and administered in a quasi-experimental field study. A pre-test–post-test survey methodology was employed to detect potential differences in privacy concerns as familiarity with the system increased. The study shows that Anglo and Hispanic subjects frame privacy issues differently associated with use of biometric technology in a fire ground accountability system. Finally, the study showed that some privacy concerns such as distrust and perceived vulnerability can be alleviated through system use with changes in post-use privacy concerns moderated by ethnic affiliation.

The Imagined Audience and Privacy Concern on Facebook: Differences Between Producers and Consumers

Facebook users share information with others by creating posts and specifying who should be able to see each post. Once a user creates a post, those who see it have the ability to copy and re-share the information. But, if the reader has a different understanding of the information in the post than the creator intended, he or she may use the information in ways that are contrary to the intentions of the original creator. This study examined whether post creators (Producers) and readers (Consumers) who are Facebook Friends had similar levels of privacy concern regarding how others might use the information in specific posts, and how their privacy concern about the post varied by whether the imagined audience consisted of Friends, Friends of Friends, or the general Public. The results showed that both Producers and Consumers had similar levels of privacy concern about a post shared with an imagined audience of Friends versus Friends of Friends. However, Consumers believed posts were more private than the Producers themselves did, and showed more privacy concern. This shows that post Consumers care about Producers’ privacy, perceive that they are co-owners of the information, and engage in boundary management with Producers.

Personalized E-Services: Consumer Privacy Concern and Information Sharing

Our purpose was to identify the behavioral characteristics and determine the attitudes of different customer segments in regard to the personalization features of e-tailers' websites as they related to the criteria of privacy concern and willingness to share information. The data of 1,659 participants were subjected to multivariate analyses of variance and discriminant analysis methods. The results indicated that the customer segment for whom it was most likely to be profitable for companies to establish a personalized e-tail strategy had a high level of privacy concern and considerable online shopping experience, were willing to share personal information, and had a low level of privacy concern. By profiling online consumers falling within these categories, our aim was to fill the gaps and address discrepancies in the current e-personalization literature by adding to the available information about consumer privacy concern and information sharing. Limitations and implications of the findings are discussed.

Russian Internet Users' Privacy: A Study of Attitudes and Behavior

There is no sufficient empirical data on Russian Internet users’ level of concern, their attitudes about online privacy, or their corresponding behavior. This research tries to remedy the shortage. As the study demonstrates, the level of privacy concern in Russia is rather mixed: users are divided equally on whether they feel worried or not about the confidentiality of their personal data online. They also don’t demonstrate a clear trust preference in online or offline environments as far as the protection of their data is concerned. Their level of worry about online privacy in the last year has significantly increased, and that increase could have been caused by media coverage of many recent privacy leaks.Factors like frequency of the Internet use, age, material status and education have an effect on users’ attitude and behavior. For example, despite a common perception that young people do not care about their privacy, there is evidence that the younger generation is not indifferent to their privacy and their identity. Users with a higher material status tend to feel less worried about their privacy, but at the same time they are more likely to take certain actions to protect their data. Finally, the paper suggests several regulatory and educational measures that would help users make informed decisions, and offers some ideas to businesses to adjust their data gathering practices.

An automatically privacy setting algorithm based on Rasch model

In the application of mobile network and internet of things (IOT), users often set sensitive information to avoid the privacy disclosing. But sometimes users are not sure whether or not to set the sensitive information open or which item should be set open. An automatically privacy setting algorithm based on Rasch model with new parameters is proposed to solve the privacy settings automatically. The proposed algorithm statistically analyses the collected users' settings information and get the summary of each user's privacy rate and privacy settings. So, new users with their privacy concern levels can find the closest privacy rate and their best privacy settings in the summary table.