IEEE Technology and Society Magazine - June 2016 - 76

targeted marketing [27]. Google's service appears
to be free to users but in truth is bought with the
user's information. This information is collected
from the user with their permission because when
using Goo g le's ser v ice s user s must a g ree to
Google's privacy policy.
This new method of advertising was so successful
that many online platforms began to follow Google's
lead. Up until Google changed the game, many of
the popular platforms promised users complete pri-
vacy by vowing in their privacy policies to not collect
any of the information generated by the user on their
platform [45]. This began to quickly change as vari-
ous web platforms started to alter their privacy poli-
cies with most of their users unaware that they had
been altered.
The users of web platforms started to gain aware-
ness of the erosion of their privacy when Edward
Snowden revealed the massive United States govern-
ment National Security Agency (NSA) surveillance
program in June 2013. The increase in online priva-
cy concerns has been staggering [13]. This revelation
called into question of the way private information of
users is handled by many of the nation's largest
technical star tups including Facebook, T witter,
LinkedIn, and Google. Thankfully for the companies,
the majority of the backlash has landed on the U.S.
NSA. However, the results of the privacy policy
changes they implemented does not put the compa-
nies on the side of the users. Much of the data gath-
ered by the NSA was actually first gathered from
popular web platforms with the consent of Internet
users thanks to privacy agreements [27]. Many priva-
cy agreements today end up going unnoticed as
users quickly click the "submit" button without
thinking to read through the terms and conditions
first [37]. This leads to the question:
R1: If users actually read the privacy agreements
would they still willingly agree to terms that severely
violate their privacy?
The first step to answering this question is to exam-
ine the content of privacy policies and assess user's
ability to understand the content. If the user does not
understand the privacy policy, there is no informed con-
sent when accepting the conditions. This inability to
comprehend the policy could also act as a deterrent to
reading the entire policy. At this point nearly every web
platform has some type of privacy policy. We will focus
on four of the most popular web platforms currently in
use: Google, LinkedIn, Twitter, and Facebook. In this
work, we focus on addressing the first step to answering
our research question by analyzing the content of the
four privacy policies and conducting a readability analy-
sis on each policy.

76

Research Contributions
We summarize our main research contributions as fol-
lows.
■ We analyze privacy agreements from four of the
most popular web platforms (i.e., Google, LinkedIn,
Twitter, and Facebook).
■ We compare and contrast the privacy agreements to
identify the platform that gathers the most informa-
tion and the platform that offers the most informa-
tion privacy for the user.
■ We analyze the privacy policies in order to deter-
mine what the average user can comprehend.
■ We recommend some potential solutions for users
to increase their privacy in spite of these agree-
ments.
■ Finally we identify future research opportunities
aimed at protecting consumer privacy.

Related Work
Privacy policies have been the focus of many researchers
over the years as the Internet has become more populat-
ed by various companies. Many past studies have
focused on privacy policies in general, rather than on
only a few web platforms as we do in this article. Also,
prior research has examined one type of privacy policy at
a time. Graber et al. [18] examined the privacy policies of
80 different Internet health web platforms. Lewis et al.
[32] decided to focus on the financial industry by examin-
ing 75 different online companies. The privacy policies
selected were comprised of an equal number of banks,
credit counseling companies, and check cashing compa-
nies. The primary focus of both of these studies was to
analyze the readability of the privacy policies. The
researchers concluded in both cases that privacy policies
from these groups were not easily understood by the
majority of users and are not considered a good measure
by which to inform the user of their privacy rights [18],
[32]. Caramujo and Rodrigues Da Silva [4] was one of the
few efforts that came closest to our objectives in this
paper, as they focused on Facebook and LinkedIn. How-
ever, they did not study other popular platforms such as
Google and Twitter and did not conduct an in depth anal-
ysis of the privacy policies. Rather these researchers
used the privacy policies to inform their proposal of a pri-
vacy-aware unified modeling language profile [4].
Our approach for analyzing the privacy policies is dif-
ferent from the efforts of other researchers [4], [18], [32],
[42], [44] since we include a side by side comparison,
readability analysis, and what these mean for the users
of these platforms. Our readability analysis uses a simi-
lar approach to [18] and Lewis et al. [32], since we use
the Flesch-Kincaid Grade Level Readability Formula. The
Flesch-Kincaid Grade Level Readability Formula mea-
sures the grade level a text is written at by analyzing

IEEE Technology and Society Magazine

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