Control your Facebook: An analysis of online privacy literacy

For an effective and responsible communication on social network sites (SNSs) users must decide between withholding and disclosing personal information. For this so-called privacy regulation, users need to have the respective skills—in other words, they need to have online privacy literacy. In this study, we discuss factors that potentially contribute to and result from online privacy literacy. In an online questionnaire with 630 Facebook users, we found that people who spend more time on Facebook and who have changed their privacy settings more frequently reported to have more online privacy literacy. People with more online privacy literacy, in turn, felt more secure on Facebook and implemented more social privacy settings. A mediation analysis showed that time spend on Facebook and experience with privacy regulation did not per se increase safety and privacy behavior directly, stressing the importance of online privacy literacy as a mediator to a safe and privacy-enhancing online behavior. We conclude that Internet experience leads to more online privacy literacy, which fosters a more cautious privacy behavior on SNSs.     

Interplay between trust,information privacy concerns and behavioural intention of users on online social networks

Trust and privacy features of websites have evolved as an important concern for any businesses or interactions, particularly in online networks. The study investigates the relationship between trust, privacy concerns and behavioural intention of users on the social network. The behavioural intention of users on the online social network (OSN) is captured by intention to disclose information and intention to interact with others in OSN. The study was conducted on a sample of 457 active users from one of the major social networking website, Facebook. Partial least squares based structural equation modelling was used for analysing the results. The findings of the study reveal that intention to disclose information mediates the relationship between trust in the website and the intention to interact with others. Another important finding of the study indicates that prior positive experience with the website significantly impacts the trust in website, and the trust in website also plays a crucial role while determining the information privacy concerns in the OSN.     

A privacy self-assessment framework for online social networks

During our digital social life, we share terabytes of information that can potentially reveal private facts and personality traits to unexpected strangers. Despite the research efforts aiming at providing efficient solutions for the anonymization of huge databases (including networked data), in online social networks the most powerful privacy protection “weapons” are the users themselves. However, most users are not aware of the risks derived by the indiscriminate disclosure of their personal data. Moreover, even when social networking platforms allow their participants to control the privacy level of every published item, adopting a correct privacy policy is often an annoying and frustrating task and many users prefer to adopt simple but extreme strategies such as “visible-to-all” (exposing themselves to the highest risk), or “hidden-to-all” (wasting the positive social and economic potential of social networking websites). In this paper we propose a theoretical framework to i) measure the privacy risk of the users and alert them whenever their privacy is compromised and ii) help the users customize semi-automatically their privacy settings by limiting the number of manual operations. By investigating the relationship between the privacy measure and privacy preferences of real Facebook users, we show the effectiveness of our framework.     

The Taste for Privacy: An Analysis of College Student Privacy Settings in an Online Social Network

The rapid growth of contemporary social network sites (SNSs) has coincided with an increasing concern over personal privacy. College students and adolescents routinely provide personal information on profiles that can be viewed by large numbers of unknown people and potentially used in harmful ways. SNSs like Facebook and MySpace allow users to control the privacy level of their profile, thus limiting access to this information. In this paper, we take the preference for privacy itself as our unit of analysis, and analyze the factors that are predictive of a student having a private versus public profile. Drawing upon a new social network dataset based on Facebook, we argue that privacy behavior is an upshot of both social influences and personal incentives. Students are more likely to have a private profile if their friends and roommates have them; women are more likely to have private profiles than are men; and having a private profile is associated with a higher level of online activity. Finally, students who have private versus public profiles are characterized by a unique set of cultural preferences—of which the “taste for privacy” may be only a small but integral part.     

What drives you to check in on Facebook? Motivations,privacy concerns,and mobile phone involvement for location-based information sharing

Given the popularity of checking in at a location via mobile phone, little research has examined the germane motivations tied to location check-in as a form of in-group electronic word-of-mouth and its relation to the concern of privacy. A survey with 255 college students found that the students' privacy concerns – both online and Facebook specific – did not show any relationship with the motivations of location check-in as a means of information sharing. However, the relationship varied among the non-users of location check-in on Facebook. Involvement with mobile phone showed mixed relationships with check-in motivations – commitment to Facebook, self-development and reputation, and promotional viral communication. Findings not only confirm that young Facebook users are relatively free from the concern of privacy during their location-based information sharing, but also suggest different motivational mechanisms to operate for Facebook users’ viral communication depending on the habitualness of their mobile phone use. Implications are discussed for interpersonal marketing strategies on social networking sites.     

Not Even Past: Information Aging and Temporal Privacy in Online Social Networks

Online social networks (OSNs) make information accessible for unlimited periods and provide easy access to past information by arranging information in time lines or by providing sophisticated search mechanisms. Despite increased concerns over the privacy threat that is posed by digital memory, there is little knowledge about retrospective privacy: the extent to which the age of the exposed information affects sharing preferences. In this article, we investigate how information aging impacts users’ sharing preferences on Facebook. Our findings are based on a between-subjects experiment (n = 272), in which we measured the impact of time since first publishing an OSN post on its sharing preferences. Our results quantify how willingness to share is lower for older Facebook posts and show that older posts have lower relevancy to the user’s social network and are less representative of the user’s identity. We show that changes in the user’s social circles, the occurrence of significant life changes and a user’s young age are correlated with a further decrease in the willingness to keep sharing past information. We discuss our findings by juxtaposing digital memory theories and privacy theories and suggest a vision for mechanisms that can help users manage longitudinal privacy.     

Shall I post this now? Optimized,delay-based privacy protection in social networks

Despite the several advantages commonly attributed to social networks such as easiness and immediacy to communicate with acquaintances and friends, significant privacy threats provoked by unexperienced or even irresponsible users recklessly publishing sensitive material are also noticeable. Yet, a different, but equally significant privacy risk might arise from social networks profiling the online activity of their users based on the timestamp of the interactions between the former and the latter. In order to thwart this last type of commonly neglected attacks, this paper proposes an optimized deferral mechanism for messages in online social networks. Such solution suggests intelligently delaying certain messages posted by end users in social networks in a way that the observed online activity profile generated by the attacker does not reveal any time-based sensitive information, while preserving the usability of the system. Experimental results as well as a proposed architecture implementing this approach demonstrate the suitability and feasibility of our mechanism.     

Minimizing information disclosure to third parties in social login platforms

Over the past few years, a large and ever increasing number of Web sites have incorporated one or more social login platforms and have encouraged users to log in with their Facebook, Twitter, Google, or other social networking identities. Research results suggest that more than two million Web sites have already adopted Facebook’s social login platform, and the number is increasing sharply. Although one might theoretically refrain from such social login features and cross-site interactions, usage statistics show that more than 250 million people might not fully realize the privacy implications of opting-in. To make matters worse, certain Web sites do not offer even the minimum of their functionality unless users meet their demands for information and social interaction. At the same time, in a large number of cases, it is unclear why these sites require all that personal information for their purposes. In this paper, we mitigate this problem by designing and developing a framework for minimum information disclosure in social login interactions with third-party sites. Our example case is Facebook, which combines a very popular single sign-on platform with information-rich social networking profiles. Whenever users want to browse to a Web site that requires authentication or social interaction using a Facebook identity, our system employs, by default, a Facebook session that reveals the minimum amount of information necessary. Users have the option to explicitly elevate that Facebook session in a manner that reveals more or all of the information tied to their social identity. This enables users to disclose the minimum possible amount of personal information during their browsing experience on third-party Web sites.     

Anonymizing popularity in online social networks with full utility

With the rapid growth of social network applications, more and more people are participating in social networks. Privacy protection in online social networks becomes an important issue. The illegal disclosure or improper use of users’ private information will lead to unaccepted or unexpected consequences in people’s lives. In this paper, we concern on authentic popularity disclosure in online social networks. To protect users’ privacy, the social networks need to be anonymized. However, existing anonymization algorithms on social networks may lead to nontrivial utility loss. The reason is that the anonymization process has changed the social network’s structure. The social network’s utility, such as retrieving data files, reading data files, and sharing data files among different users, has decreased. Therefore, it is a challenge to develop an effective anonymization algorithm to protect the privacy of user’s authentic popularity in online social networks without decreasing their utility. In this paper, we first design a hierarchical authorization and capability delegation (HACD) model. Based on this model, we propose a novel utility-based popularity anonymization (UPA) scheme, which integrates proxy re-encryption with keyword search techniques, to tackle this issue. We demonstrate that the proposed scheme can not only protect the users’ authentic popularity privacy, but also keep the full utility of the social network. Extensive experiments on large real-world online social networks confirm the efficacy and efficiency of our scheme.     

Detecting and predicting privacy violations in online social networks

Online social networks have become an essential part of social and work life. They enable users to share, discuss, and create content together with various others. Obviously, not all content is meant to be seen by all. It is extremely important to ensure that content is only shown to those that are approved by the content’s owner so that the owner’s privacy is preserved. Generally, online social networks are promising to preserve privacy through privacy agreements, but still everyday new privacy leakages are taking place. Ideally, online social networks should be able to manage and maintain their agreements through well-founded methods. However, the dynamic nature of the online social networks is making it difficult to keep private information contained. We have developed $\mathcal{PROTOSS}$ , a run time tool for detecting and predicting $\mathcal{PR}\mathrm{ivacy}\ \mathrm{vi}\mathcal{O}\mathrm{la}\mathcal{T}\mathrm{ions}\ \mathrm{in}\ \mathcal{O}\mathrm{nline}\ \mathcal{S}\mathrm{ocial}\ \mathrm{network}\mathcal{S}$ . $\mathcal{PROTOSS}$ captures relations among users, their privacy agreements with an online social network operator, as well as domain-based semantic information and rules. It uses model checking to detect if relations among the users will result in the violation of privacy agreements. It can further use the semantic information to infer possible violations that have not been specified by the user explicitly. In addition to detection, $\mathcal{PROTOSS}$ can predict possible future violations by feeding in a hypothetical future world state. Through a running example, we show that $\mathcal{PROTOSS}$ can detect and predict subtle leakages, similar to the ones reported in real life examples. We study the performance of our system on the scenario as well as on an existing Facebook dataset.     

Factors affecting privacy disclosure on social network sites: an integrated model

The self-disclosure of personal information by users on social network sites (SNSs) play a vital role in the self-sustainability of online social networking service provider platforms. However, people’s levels of privacy concern increases as a direct result of unauthorized procurement and exploitation of personal information from the use of social networks which in turn discourages users from disclosing their information or encourages users to submit fake information online. After a review of the Theory of Planned Behavior (TPB) and the privacy calculus model, an integrated model is proposed to explain privacy disclosure behaviors on social network sites. Thus, the aim of this paper is to find the key factors affecting users’ self-disclosure of personal information. Using privacy calculus, the perceived benefit was combined into the Theory of Planned Behavior, and after some modifications, an integrated model was prescribed specifically for the context of social network sites. The constructs of information sensitivity and perceived benefit were redefined after reviewing the literature. Through a study on the constructs of privacy concern and self-disclosure, this article aims at reducing the levels of privacy concern, while sustaining online transactions and further stimulating the development of social network sites.     

Online social networks: Why do students use facebook?

The growth and popularity of online social networks has created a new world of collaboration and communication. More than a billion individuals around the world are connected and networked together to create, collaborate, and contribute their knowledge and wisdom. Despite the importance of online social networks, there is relatively little theory-driven empirical research available to address this new type of communication and interaction phenomena. In this paper, we explored the factors that drive students to use online social networks (e.g., Facebook). Specifically, we conceptualized the use of online social networks as intentional social action and we examined the relative impact of social influence, social presence, and the five key values from the uses and gratification paradigm on We-Intention to use online social networks. An empirical study of Facebook users (n = 182) revealed that We-Intention to use online social networks is strongly determined by social presence. Among the five values, social related factors had the most significant impact on the intention to use. Implications for research and practice are discussed.     

Disclosures about important life events on Facebook: Relationships with stress and quality of life

The current study examined the relationship between general perceived levels of stress, quality of life, social networking usage, and disclosing important life events on Facebook in order to better understand the complex relationship between online disclosure and individual well-being. An online survey was completed by adult Facebook users aged 18–70. Results indicate that the more time spent on and the more social network memberships, the higher stress and lower quality of life; Facebook-specific usage was unrelated to either well-being variable. Together, these findings suggest that the current increase in social media variety and usage may be detrimental to user well-being. Users who shared important, bad health news on Facebook had higher stress and lower quality of life than those who did not, with no significant differences for sharing good health news. The more that users did not share important news on Facebook for self-protection and friend unresponsiveness reasons, the greater their stress. The self-protection reason was also negatively related to quality of life. These inconsistent findings can likely be partially explained by the nature of the information that is shared. These findings are discussed in light of disclosure and relationship patterns on social networks.     

When ‘friends’ collide: Social heterogeneity and user vulnerability on social network sites

The present study examines how the use of social network sites (SNS) increases the potential of experiencing psychological, reputational and physical vulnerability online. From our theoretical perspective, concerns over the use of social network sites and online vulnerability stem from the ease with which users can amass large and diverse sets of online social connections and the associated maintenance costs. To date most studies of online vulnerability have relied on self-report measures, rarely combining such information with user's validated digital characteristics. Here, for a stratified sample of 177 UK-based Facebook users aged 13 to 77, digitally derived network data, coded for content and subjected to structural analysis, were integrated with self-report measures of social network heterogeneity and user vulnerability. Findings indicated a positive association between Facebook network size and online vulnerability mediated by both social diversity and structural features of the network. In particular, network clustering and the number of non-person contacts were predictive of vulnerability. Our findings support the notion that connecting to large networks of online ‘friends’ can lead to increasingly complex online socialising that is no longer controllable at a desirable level.     

Saving face on Facebook: privacy concerns,social benefits,and impression management

The nearly ubiquitous use of online social networks generally entails substantial personal disclosure and elicits significant privacy concerns. This research uses Social Exchange Theory and the impression management (IM) literature to examine how privacy concerns can be counterbalanced by the perceived social benefits afforded by a social network’s ability to support IM. We frame social network use as an attempt to engage in IM, and we highlight the importance of a social network’s IM affordances in predicting social benefits from, and disclosure through, a social network. We test our model with a sample of 244 Facebook users, finding support for the proposed relationships and yielding the following contributions. First, this research provides a novel positioning of perceived IM affordances as a primary driver of both perceived social benefits and IM disclosure propensity. Second, this research illuminates that trust in both the social network provider and social network peers influences privacy concerns, social benefits, and perceived IM affordances. Our theory has important implications for researchers and practitioners interested in privacy issues within social networks.     

Personality and social characteristics of Facebook non-users and frequent users

Facebook is currently the largest social networking website with an estimated one billion of monthly active users in 2012. While most of the prior research has explored characteristics of Facebook users, less is known about the characteristics of individuals who do not use Facebook. The current study examined personality and social factors that might influence the decision to use Facebook and explored differences between Facebook non-users and frequent users. Online questionnaires examining levels of trust and self-disclosure, number of intimate friendships, peer usage of Facebook and scores on overt and covert narcissism were used for the purpose of the study. The results showed that non-users and frequent users differed on several social and personality characteristics. Facebook non-users had lower tendency to self-disclose, fewer peers participating in the social network and higher covert narcissistic traits. Frequent Facebook users scored higher on overt narcissism and reported more intimate friendships than non-users, indicating that close friendships might actually extend to social networks and contribute to a feeling of closeness and intimacy between friends in both an online and offline context.     

Managing privacy boundaries together: Exploring individual and group privacy management strategies in Facebook

Most research on privacy management within the context of social network sites (SNSs) treats users as individual owners of private information. Privacy, however, is beyond individual control and is also managed on a group level. This study applies the Communication Privacy Management theory (CPM) to explore the individual and group privacy management strategies in Facebook. We present a survey completed by 900 members of a youth organization regarding their online behaviors and membership. We found that women are more likely to employ individual privacy management strategies, while men are more likely to employ group privacy management strategies. For group privacy management, we found common bond and the role an individual is attributed within the youth organization to be the strongest predictors. The results generated from this study are a first but important step to illustrate the differences and similarities between individual and group privacy management. We argue that it is necessary to further study and understand group privacy to better approach users’ privacy needs.     

社交网络中用户隐私推理与保护研究综述

如今微博和Twitter等社交网络平台被广泛地用于交流、创建在线社区并进行社交活动。用户所发布的内容可以被推理出大量隐私信息,这导致社交网络中针对用户的隐私推理技术的兴起。利用用户的文本内容及在线行为等知识可以对用户进行推理攻击,社交关系推理和属性推理是对社交网络用户隐私的两种基本攻击。针对推理攻击保护机制和方法的研究也在日益增加,对隐私推理和保护技术相关的研究和文献进行了分类并总结,最后进行了探讨和展望。     

Expectations of privacy and trust: examining the views of IT professionals

The growth of interactive online lifestyles and social networks has arguably left IT users more exposed to privacy breaches. While governments continue to revise privacy legislation, the issue of online business relationships and privacy expectations remain contentious. Indeed, fewer studies have explored the expectations of users who willingly and knowingly engage in online activities that carry privacy risks. In this study, we examine the expectations and attitudes towards online privacy of a select group of 102 IT professionals. Using a qualitative survey, we show that these users have expectations of online privacy, particularly securing and protecting information from unknown third parties. Unfortunately, these expectations may go unsatisfied with third-party monitoring enabling information disclosure. In response, users argue that enhanced technical and complementary administrative measures should be actively pursued to improve privacy outcomes. The article builds further understanding of privacy expectations and trust behaviours, while exposing the importance of technical credibility from the online organisation and user perspectives.     

Mining User Knowledge for Investigating the Facebook Business Model: The Case of Taiwan Users

Social network sites (SNS), as web-based services, allow users to make open or semi-open profiles within the systems they are part of, to see lists of other people in the group and to see the relations of people within different groups. Facebook is essentially an online social network site in which individuals can share photographs, personal information, and join groups of friends. This study investigates the experiences on Facebook of various users in Taiwan. Their degrees of confidence were often demonstrated by word-of-mouth disseminations about the social network site. Further, this research looks at how the reputations of Facebook proprietors and their affiliates were disseminated through relationship marketing for formulated social network marketing in its business model concerns. Therefore, this study uses the a priori algorithm as an association rules approach, and cluster analysis for data mining. We divide Facebook users into two groups of contributors and lurkers by their profiles and then find each group’s social network community information utilization and online purchase behaviors for investigating the Facebook business models.