ArticlePDF Available

A New Privacy Paradox: Young People and Privacy on Social Network Sites

Authors:

Abstract and Figures

There is a widespread impression that younger people are less concerned with privacy than older people. For example, Facebook founder Mark Zuckerberg justified changing default privacy settings to allow everyone to see and search for names, gender, city and other information by saying “Privacy is no longer a social norm”. We address this question and test it using a representative sample from Britain based on the Oxford Internet Survey (OxIS). Contrary to conventional wisdom, OxIS shows a negative relationship between age and privacy; young people are actually more likely to have taken action to protect their privacy than older people. Privacy online is a strong social norm. We develop a sociological theory that accounts for the fact of youth concern. The new privacy paradox is that these sites have become so embedded in the social lives of users that they must disclose information on them despite the fact that these sites do not provide adequate privacy controls.
Content may be subject to copyright.
A New Privacy Paradox:
Age, youth and a theory of privacy on social media
Grant Blank
Oxford Internet Institute, University of Oxford, grant.blank@oii.ox.ac.uk
Gillian Bolsover
Oxford Internet Institute, University of Oxford, gillian.bolsover@oii.ox.ac.uk
Elizabeth Dubois
Oxford Internet Institute, University of Oxford, elizabeth.dubois@oii.ox.ac.uk
Abstract: There is a widespread impression that younger people are less protective of
their privacy than older people. For example, Facebook founder Mark Zuckerberg justified
changing default privacy settings to allow everyone to see and search for user’s names,
genders, cities and other information by saying “privacy is no longer a social norm”. Theories
of privacy generally ignore age and prior empirical research on age and privacy activity has
reached contradictory conclusions. We use multiple datasets from Britain, the United States
and Australia that uniformly show a negative relationship between age and privacy; younger
people are more likely to act to protect their privacy than older people. To account for these
findings, we develop a sociological theory that explains changes in privacy activity across the
life course. The new privacy paradox is that social network sites have become so important
that users must disclose information on them despite their privacy worries and inadequate
privacy controls.
We thank the Oxford Internet Institute and the Global Cyber Security Capacity Centre
at the University of Oxford for supporting this research. We thank William H. Dutton for
valuable comments on an earlier draft.
Blank, Bolsover and Dubois A New Privacy Paradox page 1
A New Privacy Paradox:
Age, youth and a theory of privacy on social media
On a stage in San Francisco in early 2010, Facebook founder Mark Zuckerberg said
that, as Internet users had become more comfortable sharing more information online with
more people, privacy was no longer a social norm (Johnson & Vegas, 2010). This attitude is
widely echoed by officials, the media and other major technology providers. Barnes (2006)
speaks of a privacy paradox: young people freely share personal information because they do
not fully understand the public nature of the Internet. Other researchers extend the privacy
paradox, saying people of all ages disclose large amounts of personal information online
despite expressing privacy concerns (Norberg, Horne, & Horne, 2007; Young & Quan-Haase,
2013).
The relationship between age and privacy protection is complex; parents play a large
role in shaping children’s privacy norms and practices but as young people enter adolescence
they start to develop their own privacy rules and many young people view SNSs as a place
where they should be able to share information with peers apart from their parents, teachers
and potential employers (boyd, 2014; Young & Quan-Haase, 2013). As people form families
and have children they may develop new privacy practices and people who are older, ill or
disabled may have different privacy needs (Petronio, 2012). While significant scholarly
attention has been paid to the theoretical and empirical aspects of online privacy, there is
little systematic research into how privacy activity varies by age. In fact, as we shall see,
empirical research into age and online privacy is contradictory.
Blank, Bolsover and Dubois A New Privacy Paradox page 2
This paper investigates the question, how is age related to privacy activity online? We
begin our answer by defining privacy and summarizing privacy on social network sites
(SNSs). This is followed by a review of theory and prior research about age and privacy.
Following a description of our methods, we present data on actions taken to protect privacy,
drawing on nationally representative surveys of SNS users in the United Kingdom, the
United States and Australia. The discussion section draws from these results to suggest steps
toward a sociological theory of privacy grounded in an understanding of how people organize
their social lives.
Defining privacy
Nippert-Eng defines privacy as the extent to which an “individual has the ability to
decide whether or not someone else needs to know or access something and to have her or his
wishes followed” (2010, p. 8). Similarly, Altman (1975, p. 18) describes privacy succinctly
as “selective control of access to the self”. Thus, privacy is understood as an individual’s
ability to control what personal information about them is disclosed, to whom, when and
under what circumstances.
Many theories suggest that privacy is part of the structure of social life and they
propose an understanding of privacy as contextual, with individuals selectively controlling
the access to themselves differently in different social settings. Nissenbaum describes the
notion of ‘context’ in terms of the roles, activities, norms, and values embedded in
organizations (2009, p. 133). She draws on Bourdieu’s field theory that describes social
systems in which agents (individuals) are bounded by rules (norms) in specific fields
(circumstances) (Martin, 2003). Nissenbaum (2009) also argues that the particular
characteristics of different fields create distinctive contexts, which are crucial for
understanding what is and is not a violation of privacy. These theories and related work are
Blank, Bolsover and Dubois A New Privacy Paradox page 3
valuable for understanding why people may differ in their privacy activity across different
social media platforms and contexts but they do not speak to the impact of age.
One of the few privacy theories to explicitly discuss age is Communication Privacy
Management (CPM) theory (Petronio, 2002), which suggests that privacy boundaries expand
and contract as people age. This predicts a nonlinear pattern of privacy activity: children and
elderly are least active because of their dependency on others; middle aged adults will be
most active because they have to manage the most complex relationships (Petronio, 2002,
Figure 1.3).
Goffman (1959) explains the social psychology of these issues by describing how
people act differently depending on the audience for whom they are performing. Individuals
engage in “impression management” by presenting different versions of themselves to
different audiences. The expectations and norms of the audience govern what personal
information is presented and what is kept hidden.
Privacy on social network sites
Although privacy is always an issue in everyday life, it is a particularly salient issue
on SNSs. Marwick and boyd (2011) extend Goffman’s argument to SNSs by looking at the
“imagined audiences” of users. The issue of audiences highlights a fundamental problem
with privacy on some SNSs. “Context collapse” occurs when separate offline audiences are
combined online. For example, Facebook started as a website restricted exclusively to
university students at select, elite US universities where it was bounded by the common
norms of a small, self-selected population that was relatively homogeneous in terms of age,
behavior and education. However, the site has become a transnational network with more
than 1.15 billion active monthly users of all ages (Constine, 2013) with an extremely
heterogeneous audience. Investigating the groups and networks of Finnish students and
Blank, Bolsover and Dubois A New Privacy Paradox page 4
young professionals on Facebook, Lampinen, Tamminen, and Oulasvirta (2009) find that all
users they interviewed were members of numerous explicit and implicit online groups.
The heterogeneity of SNS users means that individual users have difficulty
conceptualizing the audiences that read their online posts; so they use the same online
account to address multiple audiences at different times (Marwick & boyd, 2011; Litt 2012).
Heterogeneous contexts lead to privacy problems when actions that are appropriate in one
context are revealed to members of another audience with different social norms. For
example, a 24-year-old US high school teacher was forced to resign after a parent complained
about a photo on her Facebook profile of her holding a glass of wine and a mug of beer while
on holiday in Europe (Downey, 2011). It is important to note, however, that context collapse
is a problem for everyone on SNSs, regardless of their age. It does not explain for why
privacy activity changes with age.
Users can manage their privacy on SNSs in many ways. The most basic level is
changing privacy settings. Privacy settings differ for each SNS but normally include options
such as making one’s content public or not, making one’s profile searchable or not, and
allowing unknown others to request a connection (e.g. allow strangers to “follow” on Twitter
or to “friend” on Facebook). Some SNSs allow for a more nuanced control over access to
content. For example, Google+ “circles” allow an individual to categorize people and limit
access based on those categories. Similarly Facebook allows users to change viewing settings
for individual pieces of content, asking the question “who should see this?” Here a user can
select “Public,” “Friends,” or “more options” that include a customized list of options such as
institutional networks (e.g. University of Oxford), location (e.g. London, UK), and personally
defined groups. Privacy concerns on SNSs encourage multiple privacy protection activities
(Young and Quan-Haase, 2013; Tufekci, 2014); for example, maintaining multiple accounts,
providing false information and using aliases among others.
Blank, Bolsover and Dubois A New Privacy Paradox page 5
Possibly reflecting increasing awareness of multiple audiences, research has shown
shifting use of privacy settings. Early research in this area—conducted when Facebook was
limited to a relatively homogeneous population of elite university students—concluded that
“only a vanishingly small number of users change the (permissive) default privacy
preferences” (Gross & Acquisti, 2005). However the rapid increase in the heterogeneity of
SNS users and high levels of media coverage of privacy-related issues may have persuaded
Internet users to become more concerned about controlling their online privacy. A more
recent study finds only 36% of content is shared using the default privacy settings (Y. Liu,
Gummadi, Krishnamurthy, & Mislove, 2011) and a 2013 survey of students at a Canadian
university finds 71% of respondents report altering the access to their personal information
from the default. In a longitudinal study of Facebook users in the Carnegie Mellon Facebook
network, Stutzman, Gross and Acquisti (2013) report that between 2005 and 2011, while the
amount of personal data shared publicly decreased the amount of personal data shared with
connected profiles and silent listeners (third-party applications, advertisers and Facebook
itself) actually increased.
SNSs create privacy problems that may make users more self-consciously concerned
about their privacy than in many other online situations. This makes SNSs a particularly good
research site to investigate how people manage privacy.
In order to understand how age relates to privacy we begin with an examination of the
most basic level: the fundamental technical privacy settings provided by the SNS. These sites
justify their policies and practices based on the idea that individuals understand and utilize
the affordances they provide for managing privacy but, particularly as SNS use has become
increasingly common and privacy options increasingly complex, this may not be the case. For
instance, Vitak (2012) finds only 17% of a sample of graduate students at an American
university utilized friend lists, a primary mechanism to help prevent collapsing contexts.
Blank, Bolsover and Dubois A New Privacy Paradox page 6
Additionally while there is a large body of literature about online privacy, most
studies uses convenience samples, often of university students. The results of these studies
can speak to the opinions and practices of students, but because of their restricted age range
they cannot show us how age is related to privacy practices. Furthermore, they tell us little
about the bulk of the population who are not students but rather are employed or retired
people. We found only seven peer-reviewed papers that use a sample that can be generalized
to a broad population: Taddicken (2014) uses an Internet panel to create a sample of 2,739
German adults; Turow and Hennessy (2007) conduct a telephone survey of 1,200 US adults;
Milne and Culnan (2004) sample 2,468 US adults based on the Harris Poll Online panel; two
Pew reports (Madden & Smith 2010; Raine et al., 2013) use random digit dialing to construct
a representative sample of US adults (Litt (2013) draws from the 2010 Pew data); and a
research report by Hoofnagle, King, Li, and Turow (2010) uses a similar telephone
methodology.
Literature review
Given the diversity of SNS users and information sharing practices, it is important to
summarize prior research assessing how age relates to privacy activity. Because they are
important as control variables or as alternative explanations for our results, we also sum up
empirical findings for other demographic and non-demographic characteristics.
Age and Privacy
Empirical results for age can be quickly summarized. Sheehan (2002) constructs a
typology of online privacy concerns and finds older Internet users are more likely than
younger users to hold extreme attitudes about the importance or unimportance of online
privacy. However, Taddicken (2014) reports age has little relationship to SNS information
disclosure or concern about privacy. Similarly, Hofnagle et al. (2010) find no significant
Blank, Bolsover and Dubois A New Privacy Paradox page 7
differences by age across a range of privacy variables. However, other results contradict these
studies. Two Pew surveys find older users are less likely to change their privacy settings,
delete unwanted comments or taken other steps to limit the information about them on SNSs
(Madden & Smith, 2010; Raine et al. 2013; Litt 2013).
Other Demographic Characteristics
Other demographic variables are important in their own right and as controls for the
effects of age. Gender, in particular, is frequently related to privacy perceptions and practices
both on- and offline. Several studies report that females have higher levels of concern about
online privacy and are more likely to take action to protect their privacy than males (Lewis,
Kaufman, & Christakis, 2008; Litt, 2013; Litt & Hargittai, 2014; Peluchette & Karl, 2008).
However, a more recent study of undergraduate students’ Facebook use notes few gender
differences related to self-reported use, skills and privacy practices (boyd & Hargittai, 2010).
Possibly because of the widespread use of college student samples, the relationship
between education and privacy has been relatively neglected compared to gender (Litt, 2013).
Several studies report that individuals with higher levels of education are more concerned
about privacy (Sheehan, 2002), more likely to take action to protect their privacy online
(Milne & Culnan, 2004; O’Neil, 2001; Rainie et al, 2013) and more likely to have children
who are concerned about their online data being collected by marketers (Feng & Xie, 2014).
However, none of these studies examine how educational level may affect an individual’s
privacy activity on SNSs.
Another understudied area is income. In one of the few studies to include income,
Sheehan (2002) finds income has no significant effect on attitudes toward privacy; however,
higher income brackets were overrepresented in the sample, with almost half of respondents
earning more than $60,000 per year. In contrast, O’Neil (2001) reports Internet users with
higher incomes are less concerned with online privacy.
Blank, Bolsover and Dubois A New Privacy Paradox page 8
Non-demographic characteristics
Research into the non-demographic characteristics that may affect online privacy
practices can be broken into five main areas: computer skills, bad experiences, the number of
SNS sites used, concern about privacy and individual psychological characteristics.
Computer skills and abilities are often hypothesized to be related to online privacy
perceptions and practices: the educated and the young are often said to be more likely to
change their privacy settings because they have better skills. Turow and Hennessy (2007)
find that respondents with higher online skills have lower fear of information disclosure
online but have reduced trust in online institutions to protect their personal information.
Based on a sample of undergraduate students, boyd and Hargittai (2010) find Facebook users
with higher self-rated skills were more likely to have modified their privacy settings.
However, care must also be taken when evaluating skills (Livingstone, 2008; Young and
Quan-Haase, 2013).
Dutton and Shepherd (2006) found trust in the Internet rises with increasing
experience; however, they concluded that “with experience can come bad experiences…
which can undermine trust” (Dutton & Shepherd, 2006, p. 446). However further work found
the number of bad experiences a user had experienced had little effect on trust (Blank &
Dutton, 2012; Blank & Reisdorf, 2012; Blank, 2013). Two studies report that individuals who
had previously experienced privacy violations are more likely to take action to protect their
privacy online (Debatin, Lovejoy, Horn, and Hughes, 2009; Litt, 2013).
A third non-demographic factor sometimes cited as relevant is the number of SNS
sites used. Taddicken (2014) found that individuals with higher privacy concerns used fewer
applications but that those who used fewer applications disclosed more information. This
finding raises additional questions, such as whether those who use fewer applications tend to
Blank, Bolsover and Dubois A New Privacy Paradox page 9
have lower computer skills or whether they only use the sites that they trust to protect their
privacy?
Concern about privacy consistently shows little or no association with online
information disclosure (Taddicken, 2014). Furthermore, a psychological study of 343
undergraduate students notes that, contrary to the expectations of the authors, the propensity
to disclose information online and the propensity to control information disclosed online are
not significantly negatively correlated and are associated with different underlying
personality traits (Christofides, Muise, & Desmarais, 2009).
Another study of personality traits related to information disclosure on SNSs, C. Liu,
Ang, and Lwin (2013) finds that narcissism increased personal information disclosure and
social anxiety decreased it, among adolescent Facebook users. In contrast to previous studies
(e.g., Taddicken, 2014), the authors find privacy concerns reduce information disclosure and
they suggest that it may be a moderating factor between personality traits and information
disclosure. General levels of willingness to self-disclose are also related to online information
disclosure (Christofides et al., 2009; Taddicken, 2014).
Given that previous research has come to contradictory conclusions concerning the
effects of age (as well as gender, education, and income) on privacy activity online, it is
important to establish, based on a nationally representative dataset, the effects of these
variables on privacy related practices on SNSs in order to better understand how users are
negotiating the privacy issues associated with online platforms.
Methodology
The Oxford Internet Survey (OxIS) collects data on British Internet users and non-
users. Conducted biennially since 2003, the surveys are nationally representative random
samples of more than 2,000 individuals aged 14 and older in England, Scotland and Wales.
Blank, Bolsover and Dubois A New Privacy Paradox page 10
Interviews are conducted face-to-face by an independent survey research company. The
analyses below are restricted to the 61% of the British population who were current SNS
users in 2013 (N = 1,629) and, for longitudinal comparison, the 48% who were SNS users in
2011.
Given that we are interested in investigating the extent to which users utilise the
privacy-related affordances offered by these sites, we take as our dependent variable the
question of whether and how frequently these SNS users check or change their privacy
settings: “Thinking about all the social network sites you use, … on average how often do
you check or change your privacy settings?” For the purpose of this paper, we dichotomized
this variable into never changed versus changed privacy settings.
Among the demographic variables, place is coded as urban versus rural. Marital status
has five categories: single, married, living with partner, divorced and widowed. We also
include gender, education, age, and income (measured as total household income before tax).
The extent to which people see revealing personal information as risky has also been
found as potentially influencing their efforts to protect their privacy. Five items ask about
comfort revealing specific items of personal information: Comfort revealing an email
address, a postal address, a phone number, a date of birth or a name. A principal components
analysis indicated that these formed a single factor with a Cronbach’s alpha of 0.88 so we
used the factor scores to create a measure called “comfort revealing personal data”.
Six items ask about bad experiences on the Internet—spam, viruses, misrepresented
purchases, stolen identity, requests for bank details, and accidentally reaching a porn web
site—were summed to produce a “bad experiences” index, with values ranging from 0-6.
Concern with negative experiences was measured by creating an index from three
variables: concern with spam, viruses, or obscene or annoying emails. Each was measured on
Blank, Bolsover and Dubois A New Privacy Paradox page 11
a four-category Likert scale where 0 meant no concern at all and 3 meant very concerned.
These three variables were summed to produce an index ranging from 0 to 9.
OxIS also asks respondents whether they use each of 10 SNSs: Bebo, Facebook, an
online dating site, Google+, Instagram, LinkedIn, MySpace, Pinterest, Twitter or “any other”
SNS. These sites were chosen because other research indicated that each was used by at least
5% of the British population. The sum of these variables was used to measure “number of
SNSs used,” with a range of 0-10.
Lastly, self-reported ability using the Internet is measured in OxIS using a five-point
scale. Respondents are asked to rate their ability as bad, poor, fair, good or excellent.
During 2013, nationally representative surveys in Australia (OAIC, 2013) and the
USA (Raine et al., 2013) asked similar questions. We use the data from these surveys to
triangulate the results of our UK-based analysis. The Pew survey was the “Pew
Internet/CMU Anonymity Survey,” N = 809 Internet users. The Pew item was “Do you ever
change the privacy settings for your profile to limit what you share with others online?” The
Australian survey was the “Community Attitudes to Privacy Survey 2013” conducted by the
Office of Australian Information Commissioner (OAIC), N=1000 Internet users. The
Australian item asked “In order to protect your personal information how often, if ever, do
you adjust privacy settings on a social networking site?” Since the Australian dataset only
reports a 6-category age variable, to make the results comparable we recoded age in the Pew
and OxIS surveys to the same six categories. Because the datasets asked similar privacy
items, we can compare them to the British results to assess a possible cross-national pattern.
Results
Since our primary interest is in the relationship between age and utilizing the basic
affordances provide by SNSs to protect personal data, we begin with OxIS data from 2011
Blank, Bolsover and Dubois A New Privacy Paradox page 12
and 2013, Figure 1. The youngest age groups are the most likely to have checked or changed
their privacy settings; indeed about 80% of those aged 18-24 have checked or changed their
privacy settings compared to less than 40% of those aged 65+. Immediately this suggests that
the common belief that youth do not care and will not act on privacy concerns is potentially
wrong.
Figure 2 compares data from Britain, the USA and Australia. Despite differences in
question wording the three nations are amazingly similar. The lines are usually within the
margin of sampling error of the surveys (3-4 percentage points). The only difference is that
Australian young people report protecting their personal information more frequently than
those in the USA and UK, with only 6% of Australian 18 to 24 year olds reporting having
never adjusted their privacy settings, compared to 16-20% in the US and UK. In all three
countries young people are more, not less, likely to have acted to protect the privacy of their
personal information on social network sites. Both the UK and Australian data are consistent
with prior analyses of the US Pew data (Madden & Smith, 2010; Raine et al. 2013; Litt
2013).
0
20
40
60
80
100
% who have changed privacy settings
18-24 25-34 35-44 45-54 55-64 65+
2011 2013
OxIS SNS users age 18+: 2011 N=897; 2013 N = 1,577
Figure 1: UK SNS Users who have Changed their
Privacy Settings by Age
Blank, Bolsover and Dubois A New Privacy Paradox page 13
Multivariate models
We can compare the relative importance of different independent variables using
multivariate models. Table 1 shows odds ratios from hierarchical logistic regression models,
using the two categories of variables introduced in our literature review: demographic
variables and non-demographic variables. The dependent variable is whether or not the
respondent reported checking or changing their privacy settings. Model 1 contains only
demographic variables.
Table 1: Logistic regression models reporting odds ratios
Variable Model 1 Model 2
Age
18-24 0.166* 0.161*
25-34 0.116** 0.127**
35-44 0.122** 0.168*
45-54 0.066*** 0.094**
55-64 0.057*** 0.088**
65-74 0.027*** 0.042***
75+ 0.030*** 0.051***
Education
0
20
40
60
80
100
% who have changed settings
18-24 25-34 35-54 55-64 65+
UK 2013 USA 2013 Australia 2013
2013 SNS users: UK N = 1,321; USA N = 432; Australia N = 822
Age categories for UK and US data were recoded to be identical to Australian categories.
Figure 2: Social Media Users who have Changed
their Privacy Settings by Age (UK, USA, Australia)
Blank, Bolsover and Dubois A New Privacy Paradox page 14
Secondary school 1.410 0.950
Further education 1.753 1.159
Higher education 2.127** 1.157
Urban 0.557** 0.445***
Female 1.219 1.412*
Income
£12.5-£20,000 1.426 1.275
£20-£30,000 1.270 1.118
£30-£40,000 1.399 0.917
£40-£50,000 2.178* 1.311
£50-£80,000 1.990 1.026
Marital status
Married 0.780 1.062
Living with person 0.905 1.165
Divorced/separated 1.709 1.826
Widowed 1.068 1.171
Non-demographic variables
Comfort revealing information 1.127***
Ability to use the Internet 1.520***
Number of bad experiences 1.240**
Number of SNS sites used 1.448***
Concern with bad experiences 1.104**
Constant 15.629*** 0.360
N 1,230 1,210
McFadden's R2 8.9% 19.0%
Notes: * p < .05; ** p < .01; *** p < .001
Omitted categories are age 14-17, no educational
qualifications, rural, male, income <= £12,500/year, student,
and single.
The results from Model 1 show that after controlling for other demographic variables,
all of the age coefficients remain significant: younger people are more likely to have checked
or changed their privacy settings.1 For education, only respondents with higher education
degrees are significantly different from people with no educational qualifications. They are
over twice as likely to have checked or changed privacy settings. Respondents living in rural
1 There are various ways to specify these models. The major question is whether to include
age as a categorical variable or a continuous variable. We include age as a categorical
variable because that matches the presentation in the tables, and the Australian dataset only
provides age categories. Using the continuous version of age does not change the substantive
results.
Blank, Bolsover and Dubois A New Privacy Paradox page 15
areas are more likely to have checked or changed privacy settings. Income is generally not
significant and neither gender nor marital status are ever significant. The core takeaway from
this model is that the respondents who have checked or changed their privacy settings are
disproportionately young and well-educated. As so often on the Internet, young, educated
elites dominate.
Model 2 explores the effects of the non-demographic variables. All five of these
variables are statistically significant and they roughly double the R². The effect of the number
of social network sites used is particularly strong. Of those with only one SNS profile 49%
have changed their privacy settings compared to 81% of those with four profiles. The effect
of users’ self-reported ability using the Internet is also strong. Of those with who report only
poor ability 32% have changed their privacy settings compared to 79% of those who rate
their ability as excellent.2 The coefficients of the demographic variables do not change very
much when the non-demographic variables are added to the model. Age remains significant
and strong; urban-rural and education are also significant. However, now that some non-
demographic characteristics are controlled for, gender becomes significant; women are more
likely to have changed their privacy settings.
Discussion
We find identical results from datasets spanning three countries. In the face of
ambiguous previous research, this strikes us as a more-than-usually-persuasive result. We
noted in the literature review that two authors found no age effect (Taddicken, 2014;
Hoofnagle et al., 2010). It is important to consider how these results can be reconciled with
our finding of a strong age effect. Taddicken’s anomalous results about age could stem from
several issues. One is that Germany is different from Britain, the US or Australia. It is
2 These are marginal effects, holding all other variables at their means.
Blank, Bolsover and Dubois A New Privacy Paradox page 16
tempting, however, to look at possible methodological issues: the Internet panel was matched
on three observable characteristics: age, gender and German state. However, Taddicken
(2014, p 10) reports education levels for her sample that are almost 20 percentage points
different from the population of German Internet users. This bias could easily account for the
lack of an age effect, since we find, as many others have, that education and privacy actions
are related. Hoofnagle et al. (2010) do not ask explicit questions about SNSs, so this may
account for lack of an age effect in their findings.
We have demonstrated a strong age effect. How can we explain it? To begin with our
models test several alternative explanations. When we present these results the first
suggestion is often that young people may be more skilled at using the Internet, so they know
how to change privacy settings. When we control for skills they have a significant positive
effect but there is no change in the age effect. Age and skills are independent. This is worth
emphasizing: After controlling for skills the age effects do not change.
Another explanation is that youth are more comfortable using the Internet and thus they
are more likely to investigate and change privacy settings. Controlling for comfort level the
age effect does not change. Yet another explanation is that young people have responded to
the media attention focused on SNSs and this has made them more aware. When we control
for concern with negative effects the age effect does not change. Finally, when we control for
negative experiences we also find that the age effect does not change. None of these
alternative explanations changes the fact that the proportion of individuals who have taken
action to protect their privacy on SNSs still declines consistently by age. The age effect is not
an artifact of some other variable. It is real.
If the age effect is real, then how do we account for it theoretically? How do existing
theories explain changes in privacy concern across the life course? Existing theories do not
theorize the structural conditions under which privacy becomes important and they
Blank, Bolsover and Dubois A New Privacy Paradox page 17
understand privacy problems as something that happens to everyone, so they do not theorize
age. The closest exception is CPM Theory, which proposes that middle-aged adults should be
most privacy conscious (Petronio, 2002). Litt (2012) uses CPM but when she confronts her
finding of a negative age coefficient she says CPM “provides no explanation”. We need a
new theory that explains why privacy activity changes with age.
Toward A Sociological Theory of Privacy
We argue that privacy has its roots in broad, fundamental characteristics of social life.
This extends the prior discussions of context (Nissenbaum, 2009, 2011) and imagined
audiences (Marwick & boyd, 2011) to explain the fundamental social origins of privacy.
Taking Nissenbaum’s (2009) point that online and offline life cannot be separated, we argue
that social structure creates context: people know each other based on a broad range of shared
life stages, experiences, organizational memberships and avocations. In this sense any person
is the center of many social circles composed of people they know from different parts of
their life.3 We use the word “circle” because we do not wish to imply that these are self-
conscious entities, like a small group, and we do not use the word “network” because this is
related to technical issues such as network positions and the boundaries of various clusters
that are outside of the scope of this paper.
The offline circles of a typical individual are mostly independent and often unaware
of each other. Some circles are actively growing, like local friends when we move to a new
community, while others may be stable for years or decades, such as university friends. These
examples imply that we often have very different relationships with each of these collections
of people. We are closer to some circles than others, activities differ across circles (e.g.
3 This view of social life originates with Georg Simmel, particularly his essay “The
metropolis and the mental life” (Levine, 1971). It is also heavily indebted to Goffman’s
(1959) discussions of the problems of presentation of self and impression management across
different social contexts.
Blank, Bolsover and Dubois A New Privacy Paradox page 18
circles of friends vs. work colleagues), typical concerns also differ (e.g. neighbors vs.
family). Offline these circles generally do not conflict because different parts of our lives are
not usually exposed to each other, although some circles overlap and some people may be
part of multiple circles.
Information that is well-known and freely available in one circle (say a family) could
be embarrassing or damaging if it were to become known in another setting (such as a job).
For instance, information about health, medications or pregnancy may be shared within a
family but not with work colleagues or employers. Incidents from a vacation with friends
may not be shared with professional colleagues. Different circles have different norms for
what is acceptable and non-acceptable behavior and thus for what is made public and what is
kept private. They also have different norms for what is expected to be disclosed and what is
ordinarily private.4 For example, certain opinions about one’s job or boss that are kept to
one’s self in the office may be shared later among friends at the pub. Privacy, then, depends
on the circle, the social context out of which the circle arises and its normative expectations.
What is or should be private cannot be judged by a single standard; instead it is highly
dependent on the social context and social networking sites need to provide users with the
ability to manage their privacy in a way that meet these complex needs. This is the personal
(or interpersonal) aspect of privacy.
Privacy is further complicated because of its relationship to different institutional
domains, such as privacy with respect to corporate employers. Corporations make googling
job candidates and examining their social network websites a common practice. A 2013
4 Nissenbaum (2009, 2011) also uses the word “norm” in her discussion of privacy contexts.
However, she is concerned with two people exchanging information about a 3rd person. This
is the situation that is dealt with by laws and organizational privacy policies. In her work, the
word “norm” refers to laws and bureaucratic rules. By contrast this paper is about what
people disclose about themselves and our use of norm is more sociological, referring to
informal, often unspoken understandings about expected behavior and belief in a given social
circle.
Blank, Bolsover and Dubois A New Privacy Paradox page 19
survey of more than 2000 hiring managers and human resource professionals found that 39%
use SNSs to research job candidates and that of those who researched candidates online 43%
found information that caused them not to hire a candidate (CareerBuilder, 2013). We expect
social media to be routinely monitored by employers. People who represent themselves in
ways that could have a negative impact on employers may not be hired or may be terminated,
like Justine Sacco who was fired for a tweet about AIDS and Africa (Bercovici, 2013;
Southall, 2013). In one sense corporations could be seen as just another circle. However, this
circle is closely monitored and violations of the norms of this circle could have financial and
employment consequences.
By focusing on social structure we provide a theory that explains both the origin of
different contexts and also how contexts change. Most are created by the structure of
institutions in which we live our lives: family, work, school, church, leisure time activities
and organizations. Others come from locality: neighborhoods. As institutions change, so do
the circles that they foster; as people move from institution to institution (say, from one job to
another) so do their circles; however, these circles from former institutions tend to be
maintained online as connections on SNSs.
Privacy is uncertain, in part, because different social circles have different norms.
This is consistent with Nissenbaum’s (2011) focus on contextual integrity when considering
legal aspects of privacy. From our perspective, privacy is a special kind of social norm.
Violations to privacy can arise because of deviations from the norms of a particular social
circle, but also as a result of a difference of norms across multiple social circles. In this sense
privacy is a sort of meta-norm that arises between groups rather than within groups. It
provides a way to smooth out some of the inevitable conflicts of the varied contexts of
modern social life.
Blank, Bolsover and Dubois A New Privacy Paradox page 20
If we apply this theory to young people it predicts that they would be more concerned
about privacy than their elders. At a life stage when they are leaving their families of origin
and establishing their own identities, often young people will be doing activities in one circle
(e.g. friends) that they do not want known in other circles (e.g. potential employers or
parents) leading them to be more concerned with privacy issues. Further, children and
adolescents are likely to engage in a very limited number of social circles (for example
family, friends, school), but as an individual enters the work force, starts to pay taxes and
develops friendships and romantic relationships farther away from the home, their number of
social circles increases (e.g. work, government, relationships in new geographic locations)
increasing the potential for conflicting privacy norms. The fact that young people may join
multiple new circles in a short time compounds the possibility of privacy violations due to
inexperience or misunderstanding of the unfamiliar norms of the circles. Acquisti’s (2004)
discussions of the problem of bounded rationality are important here (see also the discussion
of uncertainty in Acquisti, Brandimarte & Loewenstein, 2015). Young people are aware of
this potential problem; Peluchette and Karl (2008) found that 20% of students would not be
comfortable with current or perspective employers seeing their Facebook profile. Similarly
boyd (2014) reports both teens and adults seek privacy in relation to those that hold power
over them, with adults concerned about privacy from corporations and governments and teens
with privacy from parents and teachers. In contrast, as individuals mature their social circles
stabilize. For example, they settle in a single location and they find permanent work. As they
grow older they gain experience and understanding of privacy norms. Protection of privacy
becomes easier because people have thought through the issues and they can apply previous
experience to solve privacy problems. This suggests why young people with rapidly
expanding social circles and rapidly changing power relations within their social contexts
could be more sensitive to privacy issues than older users. This also explains the error in
Blank, Bolsover and Dubois A New Privacy Paradox page 21
CPM theory’s prediction (Petronio 2002) that middle-aged people would be the most privacy
conscious. While CPM theory is correct that the middle-aged are involved in the largest
number of active circles, they can draw on extensive experience, so privacy management is
simpler for them than for younger, less experienced individuals.
This theory of privacy as a social construct relative to the norms of particular circles
has several implications for research. First, issues of privacy extend beyond legal definitions
of privacy and data protection, and have relevance within and between any specific social
circles. Since norms vary from circle to circle, separate circles could be studied separately.
However, we should remember that an individual’s perception of privacy online is an
inconsistent mixture of their perspectives across all social circles.
Second, we know that people have adapted their use of SNSs to mitigate lack of
privacy. What are these adaptations? How common is lying to Facebook? How often do
people set up multiple profiles for different sets of friends? Teens often go to great lengths to
creatively use social network sites in a way that maintains their privacy, such as
communicating in code, deleting posts and comments after they have read them or
deactivating their profiles during the day when adults would be looking (boyd, 2014; Young
and Quan-Haase, 2013; Tufekci, 2014). Livingston (2008) describes the use of multiple
profiles by teens as well as a careful selection of different modes of communication,
including offline, as most appropriate for communicating different personal experiences.
Studies that investigate these additional layers of privacy protection can now be considered
and expanded given our generalizable results about the most basic level of privacy protection
actions. Youth likely both use and creatively supplement basic privacy settings. The fact that
these techniques exist demonstrates that SNSs do not natively provide the affordances that
users require to maintain their privacy.
Blank, Bolsover and Dubois A New Privacy Paradox page 22
Third, we don’t really know much about the problems caused by breach of privacy.
For example, in January 2014 the theft of 4.6M SnapChat user accounts was disclosed. The
database may be sold to spam and phishing operations. The question is what are the
consequences for the people whose personal details were stolen? Are they more serious than
just additional spam? We really don’t know much about the relationship between theft of
usernames and financial loss, personal embarrassment or other potential problems. We don’t
know what the actual harm is. These would be great research topics.
Privacy may still be a strong social norm, but is often not in the commercial interest
of social media providers to cater to the differentiated nature of the norm. Instead, companies
such as Facebook stand to benefit from the sale of personal data. The real paradox is that
these sites have become so embedded in the social lives of users that to maintain their social
lives they must disclose information on them despite the fact that there is a significant
privacy risk in disclosing this information and that these sites often do not provide adequate
and transparent privacy controls to enable users to make them meet their diverse privacy
needs.
These findings lead us to conclude that there is a new “privacy paradox”. Barnes
outlined the original privacy paradox in a 2006 article arguing that “adults are concerned
about invasion of privacy, while teens freely give up personal information… (and) this occurs
because often teens are not aware of the public nature of the Internet.” While this may have
been true in 2006, it is no longer the case in 2013. Young people are much more likely than
older people to act to protect their privacy on SNSs.
We suggest that these findings are a result of the conscious choices of the individuals
who use SNSs, rather than a result of a lack of skill, a lack of understanding of privacy or
other similar variables. The new privacy paradox is not that young people do not care about
privacy but that, although they are deeply concerned about the risks of disclosing personal
Blank, Bolsover and Dubois A New Privacy Paradox page 23
information online, SNS use has become so engrained in modern life that they must use these
platforms despite the risks. This perspective finds some support in the literature. In focus
group interviews with German Internet users, Taddicken (2013) report that individuals
expressed a feeling of a strong social pressure to use SNS sites, concluding that “for many
users, refusal to participate in the social web is not perceived as a possible alternative” (2013,
p. 268). Livingston (2008, p. 406) suggests there is a “(mis)match between technological
affordances and teenage conceptions of friendship”. When she asked teenagers what they
would like to change in SNSs, their top priority was the operation of privacy settings.
The new privacy paradox, therefore, is not about young people over-sharing online
with little understanding of the risks, but that large portions of social life are now conducted
online and that SNSs do not provide users with the tools that would adequately enable them
to manage their privacy in a way that is appropriate for them. Existing theories do not
theorize the structural conditions under which privacy becomes important, and they are
unable to explain why young SNS users are more likely than their elders to utilize the
affordances of these sites, even after controlling for a variety of possible demographic and
non-demographic factors such as skill, comfort and concern about privacy. A new theory of
online privacy is necessary to start to explain the circumstances under which individual users
want to protect their online information.
Blank, Bolsover and Dubois A New Privacy Paradox page 24
REFERENCES
Acquisti, A. (2004). Privacy in electronic commerce and the economics of immediate
gratification. In Proceedings of the 4th Conference on e-Commerce (pp. 21-29). New
York: ACM.
Acquisti, A., Brandimarte, L., Loewenstein, G. (2015). Privacy and human behavior in the
age of information. Science, 347(6221), 509-514. doi: 10.1126/science.aaa1465.
Altman, I. (1975). The environment and social behavior: privacy, personal space, territory,
crowding. Brooks/Cole Pub. Co.
Barnes, S. B. (2006). A privacy paradox: Social networking in the United States. First
Monday,11(9). Retrieved from
http://firstmonday.org/ojs/index.php/fm/article/viewArticle/1394http://www.forbes.co
m/sites/jeffbercovici/2013/12/23/justine-sacco-and-the-self-inflicted-perils-of-twitter/
Bercovici, J. (2013, 23 Dec.). Justine Sacco and the Self-Inflicted Perils of Twitter. Forbes.
Retrieved 8 January 2014, from http://www.forbes.com/sites/jeffbercovici/2013/
12/23/justine-sacco-and-the-self-inflicted-perils-of-twitter/
Blank, G. (2013). Who Creates Content? Information, Communication & Society, 16(4), 590–
612. doi:10.1080/1369118X.2013.777758
Blank, G., & Dutton, W. H. (2012). Age and trust in the internet: the centrality of experience
and attitudes toward technology in Britain. Social Science Computer Review, 30(2),
135–151. doi:10.1177/0894439310396186
Blank, G., & Reisdorf, B. C. (2012). The Participatory Web. Information, Communication &
Society, 15(4), 537–554. doi:10.1080/1369118X.2012.665935
boyd, d. (2014). It’s Complicated: The Social Lives of Networked Teens. New Haven: Yale
University Press.
boyd, d., & Hargittai, E. (2010). Facebook privacy settings: Who cares? First Monday, 15(8).
Retrieved from http://journals.uic.edu/ojs/index.php/fm/article/view/3086
Burke, M., Marlow, C., & Lento, T. (2009). Feed me: Motivating newcomer contribution in
social network sites. In Proceedings of the 27th International Conference on Human
Factors in Computing Systems (pp. 945–954). New York, NY: ACM.
Brandimarte, L., Acquisti, A., & Loewenstein, G. (2013). Misplaced confidences privacy and
the control paradox. Social Psychological and Personality Science, 4(3), 340-347.
Christofides, E., Muise, A., & Desmarais, S. (2009). Information Disclosure and Control on
Facebook: Are They Two Sides of the Same Coin or Two Different Processes?
CyberPsychology & Behavior, 12(3), 341–345.
doi:10.1089/cpb.2008.0226http://articles.washingtonpost.com/2013-07-
23/politics/40862490_1_edward-snowden-nsa-programs-privacy
Constine, J. (2013, July 24). Facebook’s Q2: Monthly Users Up 21% YOY To 1.15B, Dailies
Up 27% To 699M, Mobile Monthlies Up 51% To 819M. TechCrunch. Retrieved
December 16, 2013, from http://techcrunch.com/2013/07/24/facebook-growth-2/
Debatin, B., Lovejoy, J. P., Horn, A.-K., & Hughes, B. N. (2009). Facebook and online
privacy: attitudes, behaviors, and unintended consequences. Journal of Computer-
Mediated Communication, 15(1), 83–108. doi:10.1111/j.1083-6101.2009.01494.x
Downey, M. (2011, October 10). Court rules against Ashley Payne in Facebook case. But
more to come. Atlanta Journal Constitution: Get Schooled Blog. Retrieved from
http://blogs.ajc.com/get-schooled-blog/2011/10/10/court-rules-against-ashley-payne-
in-facebook-case/
Dutton, W. H., & Meadow, R. G. (1987). A tolerance for surveillance: American public
opinion concerning privacy and civil liberties. In K. B. Levitan (Ed.) Government
infrastructures. Connecticut: Greenwood Press.
Blank, Bolsover and Dubois A New Privacy Paradox page 25
Dutton, W. H., & Shepherd, A. (2006). Trust in the Internet as an experience technology.
Information, Communication & Society, 9(4), 433–451.
Feng, Y., & Xie, W. (2014). Teens’ concern for privacy when using social networking sites:
An analysis of socialization agents and relationships with privacy-protecting
behaviors. Computers in Human Behavior, 33, 153-162.
Goffman. (1959). The presentation of the self. Harmondsworth: Penguin.
Gross, R., & Acquisti, A. (2005). Information revelation and privacy in online social
networks. In Proceedings of the 2005 ACM workshop on Privacy in the electronic
society (pp. 71–80). Retrieved from http://dl.acm.org/citation.cfm?id=1102214
Hoofnagle, C. J., King, J., Li, S., & Turow, J. (2010). How Different are Young Adults from
Older Adults When it Comes to Information Privacy Attitudes and Policies? (SSRN
Scholarly Paper No. ID 1589864). Rochester, NY: Social Science Research Network.
Retrieved from http://papers.ssrn.com/abstract=1589864
Johnson, B., & Vegas, L. (2010, January 11). Privacy no longer a social norm, says Facebook
founder. The Guardian. Retrieved 8 Jan, 2014 from
http://www.theguardian.com/technology/2010/jan/11/facebook-privacy
Lampinen, A., Tamminen, S., & Oulasvirta, A. (2009). All my people right here, right now:
management of group co-presence on a social networking site. In Proceedings of the
ACM 2009 international conference on Supporting group work (pp. 281–290). ACM.
Retrieved from http://dl.acm.org/citation.cfm?id=1531717
Levine, D. (1971). (Ed.) Georg Simmel: On Individuality and Social Forms. Chicago:
University of Chicago Press.
Lewis, K., Kaufman, J., & Christakis, N. (2008). The taste for privacy: An analysis of college
student privacy settings in an online social network. Journal of Computer-Mediated
Communication, 14(1), 79–100.
Litt, E. (2012). Knock, knock. Who’s there? The imagined audience. Journal of Broadcasting
& Electronic Media, 56(3), 330-345. doi: 10.1080/08838151.2012.705195
Litt, E. (2013). Understanding social network site users’ privacy tool use. Computers in
Human Behavior, 29, 1649-1656. doi: 10.1016/j.chb.2013.01.049
Litt, E., & Hargittai, E. (2014). Smile, snap, and share? A nuanced approach to privacy and
online photo-sharing. Poetics, 42, 1–21.
Liu, C., Ang, R. P., & Lwin, M. O. (2013). Cognitive, personality, and social factors
associated with adolescents’ online personal information disclosure. Journal of
Adolescence, 36(4), 629–638. doi:10.1016/j.adolescence.2013.03.016
Liu, Y., Gummadi, K. P., Krishnamurthy, B., & Mislove, A. (2011). Analyzing Facebook
privacy settings: User expectations vs. reality. In Proceedings of the 2011 ACM
SIGCOMM conference on Internet measurement conference (pp. 61–70). Retrieved
from http://dl.acm.org/citation.cfm?id=2068823
Livingstone, S. (2008). Taking risky opportunities in youthful content creation: teenagers’
use of social networking sites for intimacy, privacy and self-expression. New Media
& Society, 10(3), 393–411.
Madden, M., & Smith, A. (2010). Reputation management and social media. Pew Research
Center. Retrieved from http://ictlogy.net/bibciter/reports/projects.php?idp=1650
Martin, J. (2003). What is Field Theory? American Journal of Sociology. 109(1): 1-49.
Marwick, A. E., Murgia-Diaz, D., & Palfrey, J. G. (2010). Youth, Privacy and Reputation
(Literature Review) (SSRN Scholarly Paper No. ID 1588163). Rochester, NY: Social
Science Research Network. Retrieved from http://papers.ssrn.com/abstract=1588163
Marwick, A. E., & boyd, D. (2011). I tweet honestly, I tweet passionately: Twitter users,
context collapse, and the imagined audience. New Media & Society, 13(1), 114–133.
doi:10.1177/1461444810365313
Blank, Bolsover and Dubois A New Privacy Paradox page 26
Milne, G. R., & Culnan, M. J. (2004). Strategies for reducing online privacy risks: Why
consumers read (or don’t read) online privacy notices. Journal of Interactive
Marketing, 18(3), 15–29. doi:10.1002/dir.20009
Nippert-Eng, C. E. (2010). Islands of Privacy. Chicago: University Of Chicago Press.
Nissenbaum, H. (2009). Privacy in context: technology, policy, and the integrity of social
life. Stanford: Stanford UP.
Nissenbaum, H. (2011). A contextual approach to privacy online. Daedalus. 140(4): 32-48.
Norberg, P.A., Horne, D.R., Horne, D.A. (2007). The privacy paradox: Personal information
disclosure intentions versus behaviors. Journal of Consumer Affairs, 41(1), 100-126.
OAIC (Office of the Australian Information Commissioner). (2013). Community attitudes to
privacy survey. Canberra. Retrieved from
http://www.oaic.gov.au/images/documents/privacy/privacy-resources/privacy-
reports/2013-community-attitudes-to-privacy-survey-report.pdf
O’Neil, D. (2001). Analysis of Internet Users’ Level of Online Privacy Concerns. Social
Science Computer Review, 19(1), 17–31. doi:10.1177/089443930101900103
Peluchette, J., & Karl, K. (2008). Social networking profiles: an examination of student
attitudes regarding use and appropriateness of content. CyberPsychology & Behavior,
11(1), 95–97. doi:10.1089/cpb.2007.9927
Petronio, S. (2012). Boundaries of Privacy: Dialectics of Disclosure. SUNY Press.
Rainie, L., Kiesler, S., Kang, R., & Madden, H. (2013). Anonymity, Privacy, and Security
Online. Retrieved from http://www.pewinternet.org/~/media//Files/Reports/2013/
PIP_AnonymityOnline_090513.pdfhttp://thelede.blogs.nytimes.com/2013/12/20/a-
twitter-message-about-aids-africa-and-race/?_r=0
Sheehan, K. B. (2002). Toward a Typology of Internet Users and Online Privacy Concerns.
The Information Society, 18(1), 21–32. doi:10.1080/01972240252818207
Southhall, A. (2013, December 20). A Twitter message about AIDS, followed by a firing and
an apology. The New York Times. Retrieved from: http://thelede.blogs.nytimes.com/
2013/12/20/a-twitter-message-about-aids-africa-and-race/
http://thelede.blogs.nytimes.com/2013/12/20/a-twitter-message-about-aids-africa-and-
race/?_r=0http://thelede.blogs.nytimes.com/2013/12/20/a-twitter-message-about-aids-
africa-and-race/?_r=0http://thelede.blogs.nytimes.com/2013/12/20/a-twitter-message-
about-aids-africa-and-race/?_r=0Stutzman, F., Gross, R., & Acquisti, A. (2013).
Silent Listeners: The Evolution of Privacy and Disclosure on Facebook. Journal of
Privacy and Confidentiality, 4(2). Retrieved from
http://repository.cmu.edu/jpc/vol4/iss2/2
Taddicken, M. (2014). The “privacy paradox” in the social web: the impact of privacy
concerns, individual characteristics, and the perceived social relevance on different
forms of self-disclosure. Journal of Computer-Mediated Communication, 19(2), 248–
273. doi:10.1111/jcc4.12052
Taddicken, M. (2013). Privacy, surveillance and self-disclosure in the social web: exploring
the user’s perspective via focus groups. In C. Fuchs, K. Boersma, A. Albrechtslund,
& M. Sandoval (Eds.), Internet and surveillance: The challenges of Web 2.0 and
social media (Vol. 16, pp. 255–272). New York: Routledge.
Turow, J., & Hennessy, M. (2007). Internet privacy and institutional trust insights from a
national survey. New Media & Society, 9(2), 300–318.
doi:10.1177/1461444807072219
Tufekci, Z. (2014). Big Questions for Social Media Big Data: Representativeness, Validity
and Other Methodological Pitfalls. In ICWSM ’14: Proceedings of the 8th
International AAAI Conference on Weblogs and Social Media, 2014.
Vitak, J. (2012). The impact of context collapse and privacy on social network site
Blank, Bolsover and Dubois A New Privacy Paradox page 27
disclosures. Journal of Broadcasting & Electronic Media, 56(4), 451-470. doi:
10.1080/08838151.2012.732140
Young, A. L., & Quan-Haase, A. (2013). Privacy protection strategies on Facebook: the
Internet privacy paradox revisited. Information, Communication & Society, 16(4),
479–500.
... Previous research has compared demographic groups based on their privacy opinions. Whilst Han and Maclaurin [15] found online privacy concern generally increased with age, other work considered whether younger people might be better at protecting themselves due to their greater knowledge of modern technology [4]. Sheehan [30] found women to be more concerned than men, although other studies [8] have shown that male users tend to falsify their personal data more frequently. ...
... In investigating our research questions (RQ), we studied five variables: the mean amount of data disclosed (0-3), the mean privacy opinions (1-5), the mean online privacy opinions (1-5), the mean privacy self-evaluations (1)(2)(3)(4)(5), and the mean self-reported action scores (1)(2)(3)(4). This action score ranged from most to least private, with "Unsure" and "N/A" answers deemed to represent a neutral response. ...
... In investigating our research questions (RQ), we studied five variables: the mean amount of data disclosed (0-3), the mean privacy opinions (1-5), the mean online privacy opinions (1-5), the mean privacy self-evaluations (1)(2)(3)(4)(5), and the mean self-reported action scores (1)(2)(3)(4). This action score ranged from most to least private, with "Unsure" and "N/A" answers deemed to represent a neutral response. ...
Preprint
Opinion polls suggest that the public value their privacy, with majorities calling for greater control of their data. However, individuals continue to use online services which place their personal information at risk, comprising a Privacy Paradox. Previous work has analysed this phenomenon through after-the-fact comparisons, but not studied disclosure behaviour during questioning. We physically surveyed UK cities to study how the British public regard privacy and how perceptions differ between demographic groups. Through analysis of optional data disclosure, we empirically examined whether those who claim to value their privacy act privately with their own data. We found that both opinions and self-reported actions have little effect on disclosure, with over 99\% of individuals revealing private data needlessly. We show that not only do individuals act contrary to their opinions, they disclose information needlessly even whilst describing themselves as private. We believe our findings encourage further analysis of data disclosure, as a means of studying genuine privacy behaviour.
... However, privacy concern is now a less considerable matter for social media sites too. Many of them claim that they have to give less attention to these issues as we are asked by our users and even partners to provide user"s details for marketing and advertisement purposes (Blank et al., 2018). Another study also stated that privacy is a matter of one's personal human right (O"Connor & Schmidt, 2018). ...
... For this reason, they also prefer to engage less in Facebook based debates no matter how important it is to them. Study found that maintaining a profile on Facebook and adding personal information is a concern for many females (Blank et al., 2018). Many people underestimate the safety risks regarding Facebook privacy management, but women and men have a quite different opinion about it. ...
Article
Full-text available
Privacy on social networking platforms is a crucial topic, especially privacy management on a popular social media platform such as Facebook, which needs critical consideration. In this regard, this study investigated "Demographic Differences on Facebook Privacy Management." It employed a purposive sampling technique and surveyed 200 respondents. The collected data was analyzed using SPSS, including both descriptive and inferential statistics. Results indicated that the respondents revealed significant differences based on their demographics, including age and gender, in their Facebook privacy management. Therefore, everyone should be aware of privacy management. Facebook users should be made safe by the Facebook administration and their users. It is recommended that users carefully share their information on Facebook so that they do not face any infringement of their privacy rights. Finally, recommendations and limitations are discussed.
... To unlock the potential of digital health, it is critical to understand the differing perspectives on digital trust of citizens across different sociodemographic groups when designing digital health applications to optimize usability, feasibility, and adoption [25]. Like our study, other studies assessing perceptions of digital services, such as the internet or social media, have demonstrated that individuals with lower levels of education tended to be less concerned with web privacy [26,27], while those with a college or graduate degree were more likely to take additional security measures, such as encrypting emails to protect their privacy [26]. Age also influences the adoption of digital health technologies [28,29] and people's willingness to share personal health data for research, although our study did not show this. ...
... To unlock the potential of digital health, it is critical to understand the differing perspectives on digital trust of citizens across different sociodemographic groups when designing digital health applications to optimize usability, feasibility, and adoption [25]. Like our study, other studies assessing perceptions of digital services, such as the internet or social media, have demonstrated that individuals with lower levels of education tended to be less concerned with web privacy [26,27], while those with a college or graduate degree were more likely to take additional security measures, such as encrypting emails to protect their privacy [26]. Age also influences the adoption of digital health technologies [28,29] and people's willingness to share personal health data for research, although our study did not show this. ...
Article
Full-text available
Background: Combining patient-generated health data and digital health platforms may improve patient experience and population health, mitigate rising health care costs, reduce clinician burnout, and enable health equity. However, lack of trust may be a notable barrier to the data-sharing required by such platforms. Understanding sociodemographic, health, and personal characteristics will enable developers and implementers of such technologies to consider these in their technical design requirements. Objective: This study aims to understand relationships between sociodemographic characteristics of caregivers of children or adolescents and trust in and willingness to use digital platforms to store and share personal health information for clinical care and research. Methods: This study used a mixed methods approach, including surveys of caregivers of youth aged <18 years living in Canada or the United States and youth aged 16 to 17 years living in Canada, as well as web-based bulletin board discussions to further explore topics of trust in data sharing. Sociodemographic and survey data were tabulated and explored using proportional odds ordinal regression models. Comments from web-based group discussions were analyzed thematically using a coding approach to identify issues important to the participants. Results: Survey data from 1128 caregivers (female participants: n=549, 48.7%; 36-50 years old: n=660, 58.5%; Canadian: n=603, 53.5%; urban population: n=494, 43.8%) were collected, of which 685 (60.7%) completed all questions. Data from 173 youth (female participants: n=73, 42.2%; urban population: n=94, 54.3%) were collected, of which 129 (74.6%) completed all questions, and data were available for analysis. Furthermore, among 40 participants, 23 (58%) caregivers contributed to the web-based discussion boards. Related to trust, living in a rural area (vs urban; odds ratio [OR] 0.66, 95% CI 0.46-0.95) resulted in lower concern for data privacy and security, while having an undergraduate (OR 1.82, 95% CI 1.30-2.55) or graduate degree (vs secondary or trade school; OR 2.50, 95% CI 1.68-3.73) resulted in higher levels of concern. Living with a chronic disease (OR 1.81, 95% CI 1.35-2.44) increased levels of concern regarding data privacy and security. Interestingly, those with chronic disease were more willing to use digital platforms for clinical care and share personal health information for not-for-profit research. Caregivers were most concerned about data breaches involving data from their children but also highlighted that digital platforms would allow for better coordination of care for their children. Conclusions: Our research confirms the willingness of caregivers and youth to use digital platforms for both clinical care delivery and research and suggests that the value of a digital platform may outweigh the risks of its use. Engagement of end users in co-designing such platforms has the potential to enhance digital trust. However, digital trust varies across sociodemographic groups; therefore, diverse end user engagement is necessary when designing digital applications.
... For threat vulnerability, a victim of bad online experiences becomes more aware of the risks online, and therefore believes they are more vulnerable online. We created a scale measuring the number of bad experiences, following Blank et al. (2014), with a range of 0-8. Bad experiences included having personal data stolen and seeing cruel or hateful comments or images. ...
... In addition, demographic factors, such as age, were shown to influence privacy views. Blank et al. (2014) discovered that younger individuals are more inclined to take measures to safeguard their privacy compared to older individuals. These detailed observations regarding the interaction between user attitudes, social surroundings, cultural background, and education level provide useful input to the ongoing discussion on privacy protection within the framework of EVCA's UX. ...
Article
Full-text available
This research paper explores the critical aspects of User Experience (UX) in Electric Vehicle Charging Applications (EVCA) within the Chinese context. Employing a mixed-methods approach, the study identifies and validates six key UX factors: user-friendliness, payment convenience, information reliability, practical functionality, interactivity, and privacy protection. The research examines how these factors contribute to user satisfaction, emphasizing the contextual variability of user perceptions, particularly regarding privacy protection. The findings provide valuable insights for EVCA developers and operators, emphasizing the importance of user-centered design principles and the enhancement of key UX elements. The paper suggests that developers should focus on creating EVCA systems that prioritize user needs, while operators should consider user demographics and streamline operational procedures. Despite privacy protection not being a significant factor in this study, its potential to enhance user trust is recognized. The study contributes to the theoretical understanding of EVCA and offers practical guidance for improving UX in China’s rapidly evolving field of electric mobility and digital technology. It also underlines the role of policymakers in aligning policies and content with user expectations, fostering a mutually beneficial relationship between developers and users. This research advances scholarly knowledge and provides actionable recommendations for stakeholders in the electric mobility and digital technology sectors.
... Year 1986 1997 1998 2006 2008 2015 2016 embedded into our daily social lives is creating strong motivations for self-disclosure, effectively encouraging users to disclose information on themselves despite their privacy concerns, simply to keep up with their social circle and maintain their social lives [20]. Besides, in social networking sites, the rules of behaviour are mostly implicit and individuals generally foster their relationships and search for a feeling of belonging. ...
Preprint
Alice is reading a novel on her computer in the comfort of her home drinking a piña colada. Her husband John, on the other hand, is grabbing his morning cup of coffee at his favorite café while looking at his Facebook account. Alice’s webcam is on and John feels at ease using the café’s public WiFi. Then, suddenly, Alice gets an advertisement about Caribbean drinks. She is a bit perplexed. As for John, he receives an email from his boss asking why he is not at work and another from Facebook alerting him of suspicious activities on his account. He is irritated. They both thought their privacy was safe. There are a multitude of threats looming on the horizon from profiling, identity theft, and mass surveillance to depriving babies of their right to privacy before being born. Before diving into the dangers and how to eliminate or at least mitigate threats, let us understand the concept of privacy. To do so, we go back to the origins in order to comprehend its evolution throughout history. At each period, privacy practices adapt to the time-specific context. Not only that, but the historical context can have long-lasting implications for centuries to come. We then explain the situation today with the impacts on the individual and society. Finally, we draw some conclusions about the future of privacy.
... Specifically, among those with lower privacy worries, young respondents were more inclined to consent to provide their Twitter account than middle-age and older respondents, whereas for those expressing higher privacy and security considerations, younger were less likely than older to agree to link Twitter accounts. One potential reason could be that younger people, having grown up in the digital age, are more adept at managing online privacy (Blank et al., 2014), which may lead to actions more closely aligned with their privacy concerns, such as a lower rate of consent to disclose information. Furthermore, Rusk (2014) posited that trust toward the data-collecting entity may affect the association between privacy attitudes and behaviors. ...
Article
In this article, the effect of change in self-esteem level and online identity-Instagram privacy concern level on the differentiation in attitudes towards Instagram by to the social generations of individuals is discussed. The data collected from 482 respondents have been investigated mediation analysis based on the least squares method. Ordinary least square and regression model are used together as the method of the article. It has been determined that the generation directly affects the attitudes. Y generation individuals have more positive attribute towards Instagram than generation X. Similarly, generation Z has more positive Instagram attributes than generation X. The interactions between predictors are also significant. As the self-esteem decreases from generation X to Y, their positive attitudes tend to increase. This is also true for the Z compared to the X. The effect of social generation difference has also been discovered for online identity-Instagram privacy concern. This effect has been detected between the “X to Z” and “Y to Z” generations. Compared to the X, the Z generation has less online identity-Instagram privacy concern. Therefore, while social generation differences have a direct and significant effect on the attitude towards Instagram, self-esteem and privacy concerns also play important roles as mediating variables.
Preprint
Full-text available
We investigated Nigerian youths’ perception of privacy and its influence on the nature and extent of their self-disclosure on social media. Drawing on Social Penetration and Privacy Calculus theory, quantitative and qualitative content analysis of respondents’ Facebook posts was conducted for two weeks, while a survey was used to investigate privacy concerns and perceptions among 389 undergraduate students from two tertiary institutions in Kwara State. Findings revealed the manifestation of the privacy paradox among Nigerian youths and that, although the Nigerian youths had a negative perception of privacy, they engaged in habitual self-disclosure, using the relational self-disclosure mechanism.
Article
Full-text available
Over the past decade, social network sites have experienced dramatic growth in popularity, reaching most demographics and providing new opportunities for interaction and socialization. Through this growth, users have been challenged to manage novel privacy concerns and balance nuanced trade-offs between disclosing and withholding personal information. To date, however, no study has documented how privacy and disclosure evolved on social network sites over an extended period of time. In this manuscript we use profile data from a longitudinal panel of 5,076 Facebook users to understand how their privacy and disclosure behavior changed between 2005---the early days of the network---and 2011. Our analysis highlights three contrasting trends. First, over time Facebook users in our dataset exhibited increasingly privacy-seeking behavior, progressively decreasing the amount of personal data shared publicly with unconnected profiles in the same network. However, and second, changes implemented by Facebook near the end of the period of time under our observation arrested or in some cases inverted that trend. Third, the amount and scope of personal information that Facebook users revealed privately to other connected profiles actually increased over time---and because of that, so did disclosures to ``silent listeners'' on the network: Facebook itself, third-party apps, and (indirectly) advertisers. These findings highlight the tension between privacy choices as expressions of individual subjective preferences, and the role of the environment in shaping those choices.
Article
Full-text available
A large body of research argues that self-presentation strategies vary based on audience. But what happens when the technical features of Web sites enable—or even require—users to make personal disclosures to multiple audiences at once, as is often the case on social network sites (SNSs)? Do users apply a lowest common denominator approach, only making disclosures that are appropriate for all audience members? Do they employ technological tools to disaggregate audiences? When considering the resources that can be harnessed from SNS interactions, researchers suggest users need to engage with their network in order to reap benefits. The present study presents a model including network composition, disclosures, privacy-based strategies, and social capital. Results indicate that (1) audience size and diversity impacts disclosures and use of advanced privacy settings, (2) privacy concerns and privacy settings impact disclosures in varying ways; and (3) audience and disclosure characteristics predict bridging social capital.
Article
Full-text available
This paper makes three contributions: first, we suggest a clear, concise definition of Web 2.0, something that has eluded other authors, including the Tim O'Reilly the originator of the concept. Second, prior work has focused largely on the implications of Web 2.0 for producers of content, usually corporations or government agencies. This paper is one of the few analyses of Web 2.0 from the point of view of users. Third, we characterize the creative activity of Web 2.0 users. In addition to their active content production, they are unusually active users of the Internet for entertainment. In multivariate models predicting Web 2.0, the most consistently important variables are technical ability, comfort revealing personal data and, particularly, Web 2.0 confidence. These variables suggest that despite the apparent simplicity of FaceBook or of typing a book review on Amazon, ability remains very important in the eyes of users. For many, there appears to be something daunting about contributing to Web 2.0 activity and many potential users remain, rightly or wrongly, uncertain of their ability to make a contribution. We conclude that the study of Web 2.0 can tell us much about how the Internet is unique, and that it warrants a significant scholarly attention.
Article
This Review summarizes and draws connections between diverse streams of empirical research on privacy behavior. We use three themes to connect insights from social and behavioral sciences: people's uncertainty about the consequences of privacy-related behaviors and their own preferences over those consequences; the context-dependence of people's concern, or lack thereof, about privacy; and the degree to which privacy concerns are malleable—manipulable by commercial and governmental interests. Organizing our discussion by these themes, we offer observations concerning the role of public policy in the protection of privacy in the information age. Copyright © 2015, American Association for the Advancement of Science.
Conference Paper
This review of public opinion research on attitudes and beliefs about computers and privacy provides an important backdrop to current debate about the Internet and privacy. Generally, the public has long expressed concern over privacy, but demonstrate a willingness to give it away for other values and interests, from public safety to convenience.