A Digital Path to Happiness?

Applying Communication Privacy Management Theory to Mediated Interactions

Authored by: Jessica Vitak

The Routledge Handbook of Media Use and Well-Being

Print publication date:  July  2016
Online publication date:  June  2016

Print ISBN: 9781138886582
eBook ISBN: 9781315714752
Adobe ISBN: 9781317501954

10.4324/9781315714752.ch21

 

Abstract

The rise of networked publics (boyd, 2010) has changed how we interact with spouses, coworkers, friends, and others. Compared with more traditional forms of communication, smartphones and social media have created a “hyperconnected” society where instant access to people and information is now the norm. These spaces reduce temporal and geospatial constraints of communication, allowing individuals to maintain distant social ties, rekindle childhood friendships, and form new connections with others sharing common interests (for a discussion of social capital and social support resulting from Internet use, also see the chapter by Trepte and Scharkow in this volume). Networked publics also have a number of unique affordances that enable widespread dissemination, replication, and archivability of content (e.g., boyd, 2010; Treem & Leonardi, 2012), creating much larger audiences for disclosures. Consider when a world leader like President Obama tweets; with a few clicks, his thoughts are shared with millions of followers across the world, can be forwarded to those not following him (through retweets), and are archived by the U.S. Library of Congress for later retrieval (for a discussion of political participation and civic engagement in online media, also see the chapter by Bode and Riddle in this volume).

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A Digital Path to Happiness?

The rise of networked publics (boyd, 2010) has changed how we interact with spouses, coworkers, friends, and others. Compared with more traditional forms of communication, smartphones and social media have created a “hyperconnected” society where instant access to people and information is now the norm. These spaces reduce temporal and geospatial constraints of communication, allowing individuals to maintain distant social ties, rekindle childhood friendships, and form new connections with others sharing common interests (for a discussion of social capital and social support resulting from Internet use, also see the chapter by Trepte and Scharkow in this volume). Networked publics also have a number of unique affordances that enable widespread dissemination, replication, and archivability of content (e.g., boyd, 2010; Treem & Leonardi, 2012), creating much larger audiences for disclosures. Consider when a world leader like President Obama tweets; with a few clicks, his thoughts are shared with millions of followers across the world, can be forwarded to those not following him (through retweets), and are archived by the U.S. Library of Congress for later retrieval (for a discussion of political participation and civic engagement in online media, also see the chapter by Bode and Riddle in this volume).

Researchers have highlighted numerous positive social outcomes associated with the use of networked and otherwise digital technologies, including increased access to social and emotional resources (Ellison, Steinfield, & Lampe, 2007, 2011; Hampton, Goulet, Rainie, & Purcell, 2011); reduced loneliness and isolation (Cotten, Anderson, & McCullough, 2012; Deters & Mehl, 2012); relationship formation, maintenance, and enhanced relational closeness (Ledbetter et al., 2011; Smith & Duggan, 2013; Vitak, 2014); and well-being (Chan, 2015; Hampton et al., 2011; Kim & Lee, 2011; Ko & Kuo, 2009). Implicit in use of these platforms is that individuals share various types of personal information through public and private channels, including text-based content, videos, and images.

That said, networked publics are not a panacea; the same platforms that afford users opportunities for enhanced well-being also increase the potential for privacy risks and violations. Individuals may fail to consider that the actual audience for a piece of content is vastly larger than the imagined audience they target a message to (Litt, 2012; Marwick & boyd, 2011). Furthermore, the increasing diversification of userbases – and the subsequent collapsing of those networks to a single, homogenous group (e.g., Facebook “friends”) – complicates the disclosure process, in that users must consider who will see a post and how they may (mis)interpret it.

Failure to carefully balance information disclosure across all possible networks increases chances of experiencing a range of negative social, occupational, and relational outcomes. For example, the media have reported on numerous cases of young people committing suicide after being “outed” online as LGBTQ (e.g., Schwartz, 2010). Private information in the wrong hands may lead to bullying, problems at school and work, or even termination of an existing job. At the individual level, research by Kross and colleagues (2013) using experience sampling found that more Facebook use over time was associated with decline in subjective well-being, while other researchers found that negative social comparison through social media was associated with increases in depressive symptoms (Feinstein et al., 2013). Researchers have also identified an indirect link between social media use and increased stress due to the relationship between use and awareness of stressful or negative events around users; they term this “the cost of caring” (Hampton, Rainie, Lu, Shin, & Purcell, 2015).

Petronio’s Communication Privacy Management theory (Petronio, 2002; Petronio & Durham, 2015) provides a framework to address the balancing act individuals go through when making decisions to reveal or conceal a piece of private information. Building on Altman’s (1975) conceptualization of privacy as “selective control of access to the self” (p. 24), Petronio (2002) argues that people go through a “mental calculus” to assess the risks and rewards of sharing personal information. When applying CPM to media use and well-being, it becomes clear that this balancing of decisions plays a critical role in individuals’ day-to-day well-being and that significant privacy turbulence will likely have a significant negative impact on individuals. As in the example above, violating someone’s privacy by sharing a secret about their sexual preference may create widespread turbulence and have severe consequences for the person’s well-being.

This chapter considers the moderating role of privacy concerns and privacy management strategies in the relationship between individuals’ use of communication technologies and their well-being. First, I review the relationship between privacy and disclosure and the effect of information and communication technologies’ (ICTs’) affordances on this relationship. I then review the core tenets of Communication Privacy Management (CPM) theory, and describe how it can be used as an effective framework for evaluating media use and well-being and move the discussion beyond the traditional framework to account for factors specific to mediated communication channels. A brief analysis of empirical data highlights how social media users make decisions about privacy management online. The chapter concludes with reflections on ways to advance this line of research and recommendations for media effects researchers to account for the role of privacy in their studies.

Overview: Privacy and Disclosure Research

Self-disclosure features prominently in many theories of relationship development and maintenance. For example, Altman and Taylor’s (1973) Social Penetration Theory argues that partners go through four stages of relational development, with each stage characterized by increases in the depth and breadth of disclosures. Closer relationships are generally characterized by more intimate disclosures (Granovetter, 1973), but disclosures can serve a wide variety of purposes. Work by Derlega and Grzelak (1979) and Omarzu (2000) have highlighted five primary motivations behind individuals’ disclosure decision-making process: social approval, intimacy, impression management, identity clarification, and stress relief.

At the same time, researchers acknowledge that disclosures carry inherent risks (see, for example, Baxter & Montgomery, 1996; Parks, 1982). Individuals risk social rejection and hurt feelings when sharing private information; in turn, these outcomes may negatively affect their well-being. People also risk losing integrity when sharing sensitive information or information that could be easily misconstrued. This is especially likely when sharing information with a large number of people or when a private disclosure spreads beyond the intended audience, as in the case of workplace gossip or broken secrets.

The rise of ICTs has dramatically reshaped the disclosure process. Not only do these sites provide avenues to meet new people, reconnect with old friends, and maintain existing relationships, but they also afford numerous types of public and private communication exchanges that were difficult if not impossible pre-technology. For example, ICTs afford communication across space and time in new ways by minimizing the effect of physical distance between interaction partners. Social media in particular afford the ability to broadcast content to large and diverse networks of people through public sharing (Ellison & Vitak, 2015). These platforms also afford increased visibility and persistence of content, which reduces the time and energy required to locate people and information and to extend one’s network of weak ties (boyd, 2010; Treem & Leonardi, 2012).

At the core of ICTs are interactions between individuals, groups, and systems, and self-disclosure plays an important role in many of these interactions. Users of these systems share a variety of personal information through both static profile fields (e.g., birth date, location, employment) and through more interactive features such as status updates, images, and dyadic or group conversations.

In light of the public nature of many of these disclosures, researchers have increasingly focused on the tensions between self-disclosure online – which provides social and relational benefits – and protecting personal information. In one line of research stemming back to the early days of social media, researchers questioned whether a privacy paradox existed between users’ privacy attitudes and behaviors. Research on the privacy paradox posits that social media users – and especially teenagers and college students – freely share details of their personal lives while social media sites, the government, and marketers are collecting personal information for targeted advertising, homeland security, and more (Barnes, 2006). Early studies focusing on digital privacy questions suggested that even though young people claimed to have concerns about the privacy of their personal information, they publicly or semi-publicly disclosed information about their birthday, hometown, hobbies and likes, and more (Gross & Acquisti, 2005; Tufekci, 2008); this is important because researchers have proven they can predict Americans’ social security numbers with high accuracy with only one’s birth date and hometown (Acquisti & Gross, 2009). Perhaps because of normative shifts in social media use – or increased security awareness of users – more recent studies have found that individuals’ disclosure patterns are more in line with their stated privacy concerns (e.g., Stutzman, Capra, & Thompson, 2011; Vitak, 2012a). Research by the Pew Internet Project has found that, contrary to public opinion, young people do care about their privacy and digital identities; rather, it is their strategies for managing privacy and beliefs about what constitutes private information that differ from older (pre-social media) generations (Madden et al., 2013).

For all generations of ICT users, however, these new trends in information disclosure raise important questions about privacy management and the role that privacy concerns play in social and relational outcomes related to well-being. Social capital researchers have argued that ICTs provide individuals with a variety of channels for exchanging resources like social and emotional support; without disclosure of resource needs, support cannot be provided (Ellison, Vitak, Gray, & Lampe, 2014). These researchers have also found links between Facebook use over time and increases in perceived social capital for individuals with lower self-esteem (Steinfield, Ellison, & Lampe, 2008), as well as links between the amount of disclosures Facebook users make and their perceived access to social resources (Vitak, 2012a).

The link between media use, well-being, and privacy concerns is heavily context dependent (Nissenbaum, 2010), and researchers have studied ICT use and well-being across various subpopulations. For example, Best and colleagues (2016) found that young men are significantly more likely to turn to social media than government-sponsored sites for mental health support, and those who talk about their problems with online friends report greater well-being than those who do not. This is an interesting finding given that many social media users do not view social media as an appropriate place to share health or other sensitive information (Lampe, Vitak, Gray, & Ellison, 2012; Newman, Lauterbach, Munson, Resnick, & Morris, 2011). Looking at new mothers, social media enables them to stay connected with friends and interact with other women in similar situations, which in turn helps reduce feelings of loneliness and disconnection (Kim, Ahn, & Vitak, 2015; McDaniel, Coyne, & Holmes, 2012). Finally, researchers have found positive links between ICT use among older adults and reductions in depression (Cotten, Ford, Ford, & Hale, 2012), which is important because mental health becomes increasingly problematic as people’s physical and cognitive abilities decline with age.

For each of these populations, individuals must make careful decisions to balance the risks and benefits of disclosing personal information. In the next section, this tension is framed through Communication Privacy Management theory.

Theorizing Privacy and Disclosure: Communication Privacy Management

Theories of privacy have evolved over the last century, with various perspectives framing privacy as (1) a right, i.e., the right to be left alone (see Warren & Brandeis, 1890); (2) a commodity to be exchanged, as when people share their credit card information with Amazon to receive various tangible goods; (3) a temporary state characterized as “being apart from others” (Weinstein, 1971, p. 626); and (4) controlling access to the self (Altman, 1975; Westin, 1967).

In her expansion of Altman’s work, Sandra Petronio (2002) argues that individuals engage in a “mental calculus” when making decisions about whether to disclose a piece of personal information. The theory emerging from her research, Communication Privacy Management (CPM) theory, offers a framework to evaluate the dialectical tensions in private disclosures – that is, the push and pull between revealing and concealing private information. Over the years, Petronio and her colleagues have expanded the theory to include a number of assumption-based, axiomatic, and interactive maxims (see Petronio & Durham, 2015 for a review).

An important distinction between CPM and other communication theories is its framing of disclosure. As Petronio and Durham (2015) note:

CPM does not view disclosure as a unidirectional or one-dimensional communication process. Instead, disclosed private information affects both the discloser and the recipient of disclosure. After people reveal private information, all recipients are considered responsible for co-managing the information. (p. 340)

This idea – that individuals maintain “ownership” of their own private information, even if it is shared with others – is one of the core tenets of CPM. Petronio (2002; Petronio & Durham, 2015) uses the metaphor of thick versus thin boundaries to describe ownership; for example, secrets have very thick boundaries, while boundaries are much thinner for information likely to be shared with others. These boundaries are negotiated through privacy rules, which are discussed below. Once a piece of information is disclosed, the recipient(s) are “authorized” to co-own the information (Petronio & Durham, 2015). 1

With information ownership comes the belief that individuals control how their private information is shared with others. This second assumption falls squarely in line with Altman’s (1975) work on boundary management and involves negotiation of “privacy rules” to help people understand when, where, and with whom it is acceptable to share a piece of private information. Privacy rules vary based on the relationship; for example, Caughlin (2002) found that voluntary relationships (e.g., friends) are characterized by more informal guidelines than involuntary relationships like family. Furthermore, an individual’s privacy rules will vary based on cultural and contextual factors and risk–benefit calculations (Petronio, 2002). That said, privacy rules are generally flexible and adapt to changes in one’s circumstance. A canonical example of privacy rules evolving is the shift in privacy rules during a separation or divorce; not only do parties change the types of information they share with the other person, but they may also choose to reveal information to the court that was previously deemed to be private to the couple.

Finally, CPM assumes that privacy rules will break down at times, leading to turbulence between owners of a given piece of private information. Petronio and Durham (2015) note that turbulence leads to a breakdown of trust between the original owner of the information and the person(s) who violated a privacy rule. When this happens, individuals will generally recalibrate their privacy rules to avoid turbulence in the future. Turbulence can be minor, as in the case of letting a coworker know about a change in policy shortly before it is announced, to major, as reflected in the many security breaches of the 21st century. In the first case there may be no repercussions, while the latter can result in arrest, prosecution, and jail time for the people who compromised the private information. Research examining cases of mediated turbulence has found it to be a relatively common experience, with one study of young adults finding that more than one-third reported experiencing turbulence due to breakdowns in privacy rules online (Litt & Hargittai, 2014).

Extending CPM to Mediated Communication Environments

As CPM theory is grounded in communication, research applying CPM has largely focused on different types of relationships and the privacy negotiations that occur between partners. Examples of this research include romantic partners (Durham, 2008; Petronio, 2010; Petronio & Jones, 2006; Steuber & Solomon, 2011), families (Afifi & Schrodt, 2003; Petronio, Jones, & Morr, 2003; Serewicz & Canary, 2008; Toller & McBride, 2013), close friendships (McBride & Bergen, 2008), healthcare providers and patients (Petronio & Kovach, 1997; Petronio & Lewis, 2010), victims of sexual abuse (Petronio, Reeder, Hecht, & Ros-Mendoza, 1996), and students and their advisors (Thompson, Petronio, & Braithwaite, 2012).

On the other hand, few studies have applied CPM to mediated settings – even though a large proportion of communication today occurs through text messages, emails, and social media – and these studies tend to be quite narrow in scope. Child and colleagues (2011) identified various privacy management rules bloggers employed based on their current privacy needs; in a follow-up study, they identified six orientations that determine the sharing and privacy behaviors of bloggers, as well as six motives for deleting information after it was posted (Child, Haridakis, & Petronio, 2012). Similar motivations have been found in studies of Facebook users’ reasons for sharing private information (Waters & Ackerman, 2011). Finally, work by Kanter, Afifi, and Robbins (2012) found that perceptions of privacy invasions in parent–child relationships are not influenced by being connected through the site; rather, being Facebook “friends” was associated with decreased conflict between the parent and child.

Beyond addressing motivations for disclosure and managing online privacy, there are several factors researchers must account for when applying CPM to mediated spaces. First, ICTs contain a number of affordances that shape what personal information people disclose and how they disclose it. Social media platforms like Facebook, Instagram, and Twitter afford low-cost broadcasting of content to wide audiences, allowing people to extend their network far beyond traditional communication interactions (Ellison & Vitak, 2015). These technologies increase the visibility and persistence of content so that information is easier to access and can be retrieved at a later time (Treem & Leonardi, 2012). Social media may also afford status and prestige based on the virality of content and the connections one makes, as evidenced in the “micro-celebrity” trend on sites like YouTube and Twitter (Marwick & boyd, 2011).

In accounting for these affordances, CPM researchers must pay special attention to the context of a given platform to help understand how people make privacy decisions (Nissenbaum, 2010). In some cases, public sharing may be offset by the ability to interact pseudonymously, by the site’s popularity, or by the presence or absence of privacy features. Pearce and Vitak (in press) found this when studying social media use in the authoritarian nation of Azerbaijan; young people reported using Twitter over Facebook because they were able to share content without it being connected to their real name and because their family members were less likely to use Twitter.

Second, mediated communication channels focus largely on public disclosure, with Mark Zuckerberg famously declaring in 2010 that sharing – not privacy – was the new norm of interaction (Kirkpatrick, 2010). While this appears true for some users – namely teens and young adults who have grown up with social media and smartphones (boyd, 2014; Lenhart, 2015) – most users have concerns about the privacy of their information and engage in a variety of practices to protect that information. Furthermore, even though young people appear to have few concerns about sharing private information with large audiences, research suggests they make calculated decisions about who is allowed to co-own information (boyd, 2014; Madden et al., 2013; Tufekci, 2008). For older adults, privacy concerns remain a major barrier to technology adoption (Xie, Watkins, Golbeck, & Huang, 2012), with one study finding that privacy settings proved particularly difficult for older adults learning to use social media to master (Choi, Carranza, & Fox, 2013). Others may be concerned about their self-presentation across multiple audiences, which becomes difficult when network-based contexts collapse (boyd, 2010; Vitak, 2012a). This is of special concern for individuals on the job market or interacting with colleagues and friends in the same space, and many users try to keep these contexts separate or alter their self-presentation to avoid negative outcomes like the loss of a job or employment opportunity (Vitak & Kim, 2014).

Related to the second point, one’s audience for a given disclosure is not always clear. Even “private” conversations shared digitally can be captured and redistributed; Snapchat recently added a feature that allows users to save a message without notification, thus eliminating any sense of ephemerality associated with the service (Wood, 2014). Problems related to digital literacy may lead to sharing content with unintended audiences; in a qualitative study of adults aged 25–55, Vitak and Ellison (2013) found that many older users expressed confusion about Facebook’s privacy settings and, in some cases, would not share any content through the site because of privacy concerns (for a detailed discussion of media literacy as a potential moderator of the effects of media use on well-being, also see the chapter by Scharrer, Sekarasih, and Olson in this volume).

Finally, many of the negative outcomes associated with social media use can be attributed to differences between the imagined and actual audiences for content. Users generally share content with a specific audience in mind, even when sharing publicly (Marwick & boyd, 2011); these “imagined audiences” (Litt, 2012) constitute a fraction of the total audience for a post, and researchers have found that users significantly underestimate the audience size for content they share on sites like Facebook (Bernstein, Bakshy, Burke, & Karrer, 2013). While sites like Facebook and Google Plus have embedded features to allow users to segment their network, these features are generally under-utilized (Vitak, 2012a); even those who actively use these features describe them as cumbersome (Vitak & Kim, 2014). Other sites like Twitter and Pinterest have only two dissemination settings – public or private – which precludes more nuanced disclosures.

Preliminary Investigation into Digital Privacy Management

CPM is intended to be a flexible theory and supports a variety of research questions and analyses. Because privacy concerns moderate the relationship between digital media use and well-being, one way to unpack CPM is to evaluate the strategies users employ to mitigate their concerns and to understand the contextual factors that prevent engagement.

Below, I briefly discuss findings from a survey of social media users and resisters to highlight the complexities of privacy management in the digital age. Data were collected in fall 2014 from three sources: Mechanical Turk workers (including an oversampling of people without a Facebook account), a random sample of 2000 university staff, and a random sample of 2000 university undergraduates. Data are presented below in the aggregate and reflect the 1119 usable responses to the survey. The discussion of non-users (N = 286) focuses on responses to open-ended questions, while the discussion of privacy management strategies focuses on Facebook users (N = 833).

Qualitative Evaluation of Social Media Non-users’ Privacy Concerns

While the majority of social media research focuses on users’ attitudes and behaviors, a smaller subset of studies has begun examining individuals’ motivations for leaving or refusing to join sites like Facebook. For example, research by the Pew Internet Project (Rainie, Smith, & Duggan, 2013) found that 61% of current Facebook users have voluntarily taken a break from the site, largely due to a lack of time. On the other hand, Baumer and colleagues (2013) found that privacy-related concerns and issues related to time (productivity, “addiction”) were among the most commonly cited reasons for leaving or not using Facebook.

When considering the role social media play in individuals’ well-being, the prospect of leaving a site like Facebook – even for a short time – creates a disconnect between users and their network. For example, grandparents may use Facebook to see pictures of their grandchildren, while others may check the site to track friends’ birthdays. Facebook may be the only place to see this content (in the case of digital pictures) or to have it in an easily manageable format (as in the case of birthdays). The relational benefits of the site may provide users with a sense of connection and access to social and emotional resources they would not have access to otherwise (Ellison, Steinfield, & Lampe, 2007, 2011; Vitak, 2014).

So what are the reasons for leaving or resisting social media? Survey participants who reported they did not have a current Facebook account were more likely to be male, older, non-White, use fewer other social media platforms, and have lower digital skills. These participants were asked a series of open-ended questions about their non-use. Two researchers coded responses to the question, “Why have you chosen to not participate in Facebook?,” revealing eight categories of motivations. Respondents cited privacy and security concerns in their replies more often than any other reason (40%), followed by comments reflecting a lack of interest (39%). The privacy-related responses were then recoded to identify subcategories, with six main concerns emerging relating to who had access to their data, what was done with their data, personal safety, and a lack of trust in Facebook. Below, I highlight two of the more prominent themes.

The largest set of respondents expressed concerns related to how Facebook collects, uses, and shares personal data, both within the company and with third parties. For example, a 56-year-old male said, “I have no interest in playing catch-up with my privacy settings with a company whose business model is to collect as much data on me as possible.” A 45-year-old woman echoed this sentiment, saying, “Facebook is a marketing company that resells your information to the highest bidder. I do not want to participate in the marketing experiment.” These concerns reflect Altman’s (1975) and Petronio’s (2002) framing of privacy as control; when one cannot control access to personal information on a given service, it becomes less appealing to use. Facebook’s lack of transparency in this process, as well as negative media coverage regarding the company’s internal research, have amplified users’ concerns in this area. 2

While the first theme reflects concerns about the relationship between the user and the company (i.e., Facebook), a second set of comments reflected concerns about the visibility of personal information to other users. These concerns included a lack of confidence or low digital literacy in understanding who can see shared content and, more specifically, concerns about negative outcomes resulting from content being viewed by unintended audiences. For example, a 30-year-old male said, “I deleted Facebook to help control the way I am perceived professionally” while a 28-year-old male said, “I have chosen not to participate in Facebook due to a lack of overall control. While I can control the information that I personally place on the site, other people can tag me in things that I am unaware of at the time.” This is a key component of interaction in networked publics – the user is rarely in complete control of all content about herself. Rather, one’s online presence is collaboratively shaped by the user, the system, and other users. In light of CPM, the ability for other users to share private information, such as a compromising photograph, without any interaction with the person will likely violate privacy rules and lead to significant turbulence, especially if that content results in a negative outcome like a lost job or friendship.

In sum, these findings suggest that Facebook – and likely similar sites that collect personal information – faces a complex challenge in addressing both users’ and non-users’ privacy concerns. Many participants voiced concerns about sharing information on any site because of concerns related to (lack of) control and previous issues with turbulence (e.g., citing “drama” or relational conflict on the site). Different groups have different concerns, and addressing all of them sufficiently to change non-users’ negative attitudes toward ICTs will be difficult.

That said, there are a number of social and technical strategies individuals can employ to reduce turbulence and regain some degree of control over their personal information. These are discussed more in the next section.

Quantitative Variations in Facebook Users’ Engagement in Privacy Management Behaviors

In the survey, Facebook users were asked about their engagement in 14 behaviors to manage the privacy of their personal information. These items were developed based on previous studies (e.g., Lampinen, Lehtinen, Lehmuskallio, & Tamminen, 2011; Vitak & Kim, 2014) and reflect both individual versus collaborative strategies as well as social versus technical strategies. For this analysis, I focus on a composite scale of five user behaviors to limit network access or alter content before sharing with a wider audience. Items, means, and standard deviations of the Privacy Protection Strategies Scale are listed in Table 21.1.

Participants were also asked to rate their level of concern regarding 11 Facebook-specific privacy concerns (α = .92, M = 3.22, SD = 1.06) developed in previous work (Vitak, 2012b), including both site-based and network-based concerns, as well as more general concerns about privacy violations or identity theft. Finally, participants were asked the diversity of their friend network on the site, their use of other social media, and their perceived well-being (via Rosenberg’s, 1989, self-esteem scale).

One question CPM researchers explore is individual differences in privacy protection behaviors. For example, Child et al. (2011) identified five motivations for deleting blog content after posting it, including protection of personal identity, impression management, and employment security. Because Facebook’s technical structure collapses various audiences for content, users may employ a variety of strategies to protect their private information, relationships, and job security. To look for differences in engagement, a three-tiered version of the Privacy Protection Strategies Scale was created, with the categories comprised of the first, third, and fifth quintiles of response values. A one-way ANOVA identified significant differences for six variables, as shown in Table 21.2.

Table 21.1   Privacy Protection Strategies Scale (N = 833; α = .79)

Items

M

SD

Delete a status update before posting

2.63

1.10

Change the wording of a status update to avoid angering some of your Facebook friends

2.37

1.12

Post a status update to a subset of your Facebook friends so that it will not be visible to a specific user or group of friends

2.22

1.18

Block another Facebook user

2.31

1.07

Limit the amount of content a Facebook friend can see

2.67

1.21

Full Scale

2.44

.84

Item prompt: “How often do you engage in the following behaviors when using Facebook?” (Five-point scale, range: Never to Very Often).

Table 21.2   One-way ANOVA Comparing Low, Moderate, and High Engagement in Privacy Protection Strategies

Low Privacy Management

Moderate Privacy Management

High Privacy Management

Sex: Female

.42a

.63b

.57b

Age

32.73b

29.92a

28.71a

Privacy concerns

2.64a

3.17b

3.76c

Use of other social media

2.18a

2.79b

3.15b

Network diversity

7.78a

9.61c

8.84b

Self-esteem

4.15a

4.12a

4.02a

Note: Privacy Protection Scale broken into three groups based on first, third, and fifth quintiles (i.e., lowest 20%, 40–60%, and highest 20% of participant scores). Superscript letters show groupings based on Tukey’s B post hoc tests.

Results of the ANOVA suggest that women, younger adults, and more active social media users are significantly more likely to be moderate to high privacy managers. Unsurprisingly, engagement in privacy protection strategies increases with one’s privacy concerns and network diversity, although the relationship for the latter is non-linear. Finally, no relationship was found when looking at variations in self-esteem; as the survey did not include other measures of well-being, little can be inferred about the relationship between overall well-being and privacy protection strategies. 3 These results held in a OLS regression predicting engagement in privacy protection strategies and including the same variables (plus a control variable for the sample), F(7, 810) = 30.42, p <.001, adjusted R2 = .20.

Overall, quantitative results suggest there are a number of specific factors that influence privacy management on Facebook, a site driven largely by public or semi-public disclosures. The significant but non-linear findings for network diversity warrant additional research, especially in light of the significant relationship between audience size and diversity and use of Facebook friend lists, as well as with the amount of disclosures users make on the site (Vitak, 2012a). In addition, while recent research has shown a positive correlation between privacy concerns and disclosure habits (Stutzman et al., 2011; Stutzman, Vitak, Ellison, Gray, & Lampe, 2012; Vitak, 2012a), more nuanced research into how privacy concerns correlate to (1) specific types of disclosures, (2) disclosures to specific audiences, and (3) disclosures on different platforms (with different affordances and norms) is needed to fully understand how all these factors interact.

Next Steps: Where Does Privacy Fit into Well-Being Research?

As this chapter has highlighted, privacy concerns can create a significant barrier to personal disclosures in mediated spaces. Understanding how these concerns shape disclosure processes and privacy protection strategies is critical to well-being research because of the sheer amount of interactions now occurring through mediated spaces: Facebook has more than one billion daily users around the world (Facebook Stats, 2015), Snapchat boasts 60% penetration among 13- to 34-year-olds in the US (Snapchat Ads, 2015), and smartphone penetration is increasing worldwide, with 68% penetration in the US as of October 2014 (Horrigan & Duggan, 2015). These technologies allow relationship maintenance practices to occur from a distance and, for some people, may prevent more casual friendships from fading away over time (Vitak, 2014). From a social capital perspective, users cannot hope to obtain social and emotional resources if they are unwilling to disclose them in the first place (Vitak, 2012a) or engage in meaningful interactions with their network (Burke, Marlow, & Kraut, 2011; Ellison et al., 2014). From a relational perspective, users must constantly evaluate how to structure disclosures within the limitations of the medium (e.g., reduced cues; see Walther, 1992 for an overview) and the technical structure of the site (e.g., turbulence resulting from disclosures being disseminated to all contacts). When this becomes too challenging, users may decide to not participate on the site, to move to more private channels, or to self-censor their content, as in Hogan’s (2010) discussion of the lowest common denominator strategy.

Communication Privacy Management theory (Petronio, 2002) provides a useful framework through which to identify and evaluate people’s disclosure strategies when interacting in mediated spaces and to understand the moderating role privacy plays in the relationship between use of these platforms and users’ well-being. The flexibility of the theory allows incorporation of additional considerations beyond those in face-to-face communication, including social and technical affordances, the more public nature of interactions, and the collapsing of network contexts. While the original framing of CPM focused on one-to-one disclosures, the mass-personal nature of sites like Facebook require researchers to account for these factors in their study design and analysis. As Petronio (2002) notes, privacy rules will vary across contexts and groups, and this has been especially apparent with the rise of social media and changing norms around what constitutes “private” information. Researchers must acknowledge these differences in communication patterns, which represent an important contextual difference compared to face-to-face interactions.

CPM may be critiqued for being overly broad, but the theory provides a strong foundation for researching privacy, media use, and well-being. Researchers in this area must account for the role of privacy concerns in their models, whether by extending existing theories or incorporating CPM’s main components – privacy rules, privacy boundaries, and turbulence – into other models. Privacy-related factors may account for some of the variations in studies of media use and well-being in the digital age, and help further clarify under what conditions communication through networked publics is beneficial and when it may become problematic.

Notes

Note that in Petronio’s more recent work (see Petronio & Durham, 2015), she discusses “unauthorized ownership” to highlight instances where private information is shared without the owner’s consent, as in the case of third-party data aggregators.

Note that these data were collected a few months after Facebook’s “emotional contagion” study that generated significant negative attention from users.

The correlation between self-esteem and privacy concerns was also non-significant (r = −.01, p = .74).

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