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Big Data, Transparency & Social
Media Networks
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Do social media users value their data?
Transparency Issues In The Data Usage Policies of Large Social
Media Networks
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Sylvia Ogweng
University of Toronto - School of Continuing Studies
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SCS 2942 – 017

Foundations of Enterprise Data Analytics – Concepts and Controls	

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1
The phrase “if you’re not paying for it, you’re not the customer; you’re the product
being sold,” 
first appeared online in 2010 during a Metafilter discussion, and in the age1
of social media and big data, the saying has never resonated any louder.
While social media and Internet users are becoming increasingly aware of the
privacy issues surrounding their browsing, tweeting, liking and sharing habits, it has
become clear that most are not aware of the degree of surveillance that occurs during
typical social media activity.
This essay aims to examine the transparency issues that lie in data usage policies of
social media networks. While the issues at hand can apply to nearly every large-scale
social network, the analysis within this paper focuses on the big data privacy &
transparency issue within the frameworks of the current top three social networks:
Facebook, Twitter and LinkedIn.
Analysis of the major, overarching issues will first be outlined on a broader scale,
followed by their unique associations within the most relevant network. A major portion
of this final analysis will focus on the backlash from Facebook’s recent Emotion
Manipulation Study 
.2
Ultimately, this paper aims to answer a question that should be of particular
interest to social network’s as they continue to thrive as billion-dollar businesses and
amass large pools of data: does my user value transparency? Also, how should I go about
providing it?
I have selected this topic in great part to the overwhelming role that social
networks play in my own everyday life and as a digital marketer. More importantly,
despite considering myself a tech-conscious individual I find there is still much secrecy
over data manipulation through the social networks my friends, family and colleagues
engage with.
!
2
Lifehacker, http://lifehacker.com/5697167/if-youre-not-paying-for-it-youre-the-product1
Forbes, http://www.forbes.com/sites/kashmirhill/2014/06/30/facebook-only-got-permission-to-2
do-research-on-users-after-emotion-manipulation-study/
In effect, I am seeking clarification on what type of data is collected; who is seeing this
data; and how they plan to manipulate it.
!
Transparency And Current Privacy Policies
!
Achieving transparency is seemingly a lofty goal for big data social networks. There
is often a fine line between alienating current users, or attracting new ones, and
maintaining an open, honest and ethical relationships with them. Ultimately “achieving
transparency should mean that information handling practices are conveyed to users in a
way that is relevant and meaningful to the choices they must make.” 3
At first glance, an existing user would most likely conclude —assuming he or she
has already read the Privacy/Data Use Policy— that the current state of transparency
within social media network data usage policies is rather clear and concise. Policies
across Facebook, Twitter and LinkedIn have been well organized and structured in a
manner which are easy to read.
Internet Society’s Global Internet User Survey reports that only 16% of Internet users
review these policies and even worse, only 20% of those that do, understand its
contents. 
However, if they are to read them, it would likely occur at the sign up stage.4
Having signed up for each service anew there are certain transparency issues which arise
quickly. When signing up for a new Facebook account, the privacy policy link was so
small in comparison to the “Create Account” call to action that I overlooked it altogether.
Twitter slightly improves on this user interface by allowing potential users to read the
entire policy directly on the page, albeit in very small font. Lastly, LinkedIn applies a
similar sign up strategy to Facebook.
!
3
“The Age of Predictive Analytics: From Patterns to Predictions, Office of the Privacy3
Commissioner of Canada, August 2012
Lifehacker, http://lifehacker.com/5964185/do-you-read-privacy-policies-and-do-you-4
understand-them
It is worth distinguishing LinkedIn from Facebook and Twitter when evaluating
these privacy policy pages. At nearly 8,000 words, it is not the longest, however the
network has taken great care in marketing their “trust” policy. Employing icons,
embedding a video and sectioning of the content adds a sense of approachability to the
document. After thorough review of the text, three transparency issues arise. They are as
follows 
:5
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1. LinkedIn states that user information may be shared with “LinkedIn
affiliates” but does not identify the full list of affiliates or how they would, in fact, be
using the user data in detail.
!
2. When addressing data sharing with “Third Parties,” the language used to describe
these regulations changes from a casual business tone to legal and technical jargon.
!
3. The nearly 2-minute long privacy policy video found at top of the page, which is
intended to save users time by skipping the fine print, only touches upon some of
the most sensitive areas of the document and skips most sections of the policy.
!
The second and third points illustrate Helen Nissenbaum’s Transparency Paradox. As
she explains, if the policy “finely details every flow, condition, qualification, and
exception, we know that it is unlikely to be understood, let alone read. But summarizing
practices in the style of say, nutrition labels is no more helpful because it drains away
important details, ones that are likely to make a difference.” 6
While all three social networks originally began harvesting user data to drive ad
sales, as each network introduced new revenue streams, more and more of data was
4
LinkedIn Privacy Policy, http://www.linkedin.com/legal/privacy-policy.5
Nissenbaum, Helen. “ A Contextual Approach to Privacy Online,” http://www.amacad.org/6
publications/daedalus/11_fall_nissenbaum.pdf, pg 36.
being analyzed in much more sophisticated ways. These adjustments have forced social
networks to alter their policies on an on-going basis.
LinkedIn for examples, now has three main streams of revenue: premium accounts,
ad sales — which most users are aware of — and what Financial Review calls its “gold
mine”: “a suite of products created by its token solutions division and sold to corporate
clients.” 
This third stream returned $205 million dollars (US) in revenue during the7
second quarter alone of 2013.
While LinkedIn’s privacy policy is clear about advertising data use, it does not
explicitly state how its data collection contributes to the company’s “gold mine.”
!
Why Is Transparency Important?
!
Furor recently erupted when it was revealed that Facebook performed a
psychological experiment on approximately 700,000 of its users, unknowingly and
without receiving consent 
. Aimed at gaging the emotional state of its users, the social8
network tested whether a decrease of negative or positive posts would effect the type of
status updates generated by users.
Given the intense backlash reported in the media 
, it is safe to say that most users9
were not aware their activity was being monitored for network experiments. An ethics
issue clearly arises here for Facebook, but more importantly (in the context of this
paper), its transparency measure are put into question by its users, the media and
business partners. Many users and even governments questioned the legality of the
experiment and declared it unethical at its core.
!
5
Financial Review. “How LinkedIn’s using your data” http://www.afr.com/p/national/work_space/7
how_linkedin_using_your_data_G0CiiqJ3feJ4SmbTnOR7lK
Wall Street Journal. “Furor Erupts Over Facebook's Experiment on Users” http://8
online.wsj.com/articles/furor-erupts-over-facebook-experiment-on-users-1404085840
Wall Street Journal. “Furor Erupts Over Facebook's Experiment on Users” http://9
online.wsj.com/articles/furor-erupts-over-facebook-experiment-on-users-1404085840
What is even more demoralizing is that Facebook’s privacy policy at the time (2012), did
not express this type of data manipulation to its users — explicitly or implicitly:
!
“Four months after this study happened, in May 2012, Facebook made changes
to its data use policy, and that’s when it introduced this line about how it
might use your information: “For internal operations, including
troubleshooting, data analysis, testing, research and service improvement.”  10
!
Today, Facebook’s privacy policy includes the “research” declaration but does not
make explicitly clear the potential of data manipulation for experiments, let alone
psychological one. “We may use the information we receive about you for internal
operations, including troubleshooting, data analysis, testing, research and service
improvement,” 
the policy reads.11
The controversy created from this substantial lack of transparency mirrors itself
on a smaller scale for Twitter and LinkedIn. In 2013, Twitter’s Transparency Report 12
revealed that the U.S. government completes 80% of info requests, and in 2011,
LinkedIn received backlash from its users who discovered their profile image being used
in the networks ads without consent 
. Both events generated considerable backlash.13
The result which can be drawn from these public relations nightmares is twofold.
Firstly, the data usage policies of social media networks do not offer users enough
transparency. The backlash reported online indicates users are not aware of the extent of
6
forbes.com, “Facebook Added 'Research' To User Agreement 4 Months After Emotion10
Manipulation Study” http://www.forbes.com/sites/kashmirhill/2014/06/30/facebook-only-got-
permission-to-do-research-on-users-after-emotion-manipulation-study/
Facebook Privacy Policy, https://www.facebook.com/about/privacy/your-info11
Twitter Transparency Report, https://transparency.twitter.com/12
Gadgetwise Blog, New York Times. “LinkedIn’s Social-Ad Misstep” http://13
gadgetwise.blogs.nytimes.com/2011/08/17/linkedins-social-ad-misstep/?
_php=true&_type=blogs&_r=0
data manipulation which occurs. Secondly, transparency is important and highly valued
to Facebook, Twitter and LinkedIn users.
!
Solutions & The Future of Social Network Transparency
!
Many approaches can be taken to rectify social media’s lack of transparency. The
first, and rather simple, approach is to increase the privacy policy’s visibility on each
network. Rather than placing the document link in the footer, or in small font, force the
user to opt-in through interactive measures.
Secondly, I propose to educate the user on the end product of data manipulation,
not necessarily the process. While I do agree with the Office of the Privacy Commissioner
of Canada when it states, “the complex processes that underlie predictive analytics or
data mining techniques are usually quite lost on many individual, if not most,” 
the14
exact type of information which is derived from it could be easily and clearly
communicated to the user.
Lastly, users should be given the choice to control what type of information is used
for data manipulation. Allowing the ability to customize a policy introduces the element
of choice, which I believe would entice users to become more involved in the process of
privacy. This final approach, however, will impact the pool of data collected by social
networks, and most likely in a negative way. Ultimately, I believe the user must be made
aware of the value that his or her data generates.
Beyond its issues concerning privacy and transparency, what does the future of
Data look like? One last issue that arises from this discussion is the question of
asymmetric information flow: is the final exchange between free social networks and
users, a fair one? Companies such as New York-based startup Datacoup 
are likely to15
grow as users become more aware of their data’s tremendous value. Though the service
7
“The Age of Predictive Analytics: From Patterns to Predictions, Office of the Privacy14
Commissioner of Canada, August 2012
datacoup.com15
does not address issues of privacy — in fact, it may even worsen the issues at hand — it
is dubbed as the “first personal data marketplace.” The platform allows consumers to
“aggregate and sell” their anonymous personal data for $8 per month 
.16
Although talk of selling your data online has been in talks for some time now, the
idea has yet to be embraced by both consumers and retailers, who would greatly benefit
from the insights of combined spending and online activity. Datacoup CEO and
cofounder Matt Hogan touts the service as revolutionary because “few data providers can
combine traces of a person’s online activity with a record of their spending activity.” The
combination of data is said to “unlock more value, and there’s no way to do that other
than from the user themselves.”
!
——————————————————-
!
In conclusion, the usage of large social media networks combined with a lack of
transparency measures creates three major problems: users are unaware of the type of
data that is collected and being shared, how it’s being used and what results are derived
from it.
By examining Facebook’s Emotion Manipulation Study and similar situations at
Twitter and LinkedIn, it is clear that transparency on social media networks must
improve. It was concluded that transparency is important to users and, therefore, it is in
the social network’s best interest as a service providers to offer a highly-valued, ethical
and transparent experience to its users if they wish to continue their ongoing growth.
8
datacoup.com16

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Big Data, Transparency & Social Media Networks

  • 1. ! ! ! ! ! Big Data, Transparency & Social Media Networks ! Do social media users value their data? Transparency Issues In The Data Usage Policies of Large Social Media Networks ! ! ! ! ! ! ! ! Sylvia Ogweng University of Toronto - School of Continuing Studies ! SCS 2942 – 017
 Foundations of Enterprise Data Analytics – Concepts and Controls ! 1
  • 2. The phrase “if you’re not paying for it, you’re not the customer; you’re the product being sold,”  first appeared online in 2010 during a Metafilter discussion, and in the age1 of social media and big data, the saying has never resonated any louder. While social media and Internet users are becoming increasingly aware of the privacy issues surrounding their browsing, tweeting, liking and sharing habits, it has become clear that most are not aware of the degree of surveillance that occurs during typical social media activity. This essay aims to examine the transparency issues that lie in data usage policies of social media networks. While the issues at hand can apply to nearly every large-scale social network, the analysis within this paper focuses on the big data privacy & transparency issue within the frameworks of the current top three social networks: Facebook, Twitter and LinkedIn. Analysis of the major, overarching issues will first be outlined on a broader scale, followed by their unique associations within the most relevant network. A major portion of this final analysis will focus on the backlash from Facebook’s recent Emotion Manipulation Study  .2 Ultimately, this paper aims to answer a question that should be of particular interest to social network’s as they continue to thrive as billion-dollar businesses and amass large pools of data: does my user value transparency? Also, how should I go about providing it? I have selected this topic in great part to the overwhelming role that social networks play in my own everyday life and as a digital marketer. More importantly, despite considering myself a tech-conscious individual I find there is still much secrecy over data manipulation through the social networks my friends, family and colleagues engage with. ! 2 Lifehacker, http://lifehacker.com/5697167/if-youre-not-paying-for-it-youre-the-product1 Forbes, http://www.forbes.com/sites/kashmirhill/2014/06/30/facebook-only-got-permission-to-2 do-research-on-users-after-emotion-manipulation-study/
  • 3. In effect, I am seeking clarification on what type of data is collected; who is seeing this data; and how they plan to manipulate it. ! Transparency And Current Privacy Policies ! Achieving transparency is seemingly a lofty goal for big data social networks. There is often a fine line between alienating current users, or attracting new ones, and maintaining an open, honest and ethical relationships with them. Ultimately “achieving transparency should mean that information handling practices are conveyed to users in a way that is relevant and meaningful to the choices they must make.” 3 At first glance, an existing user would most likely conclude —assuming he or she has already read the Privacy/Data Use Policy— that the current state of transparency within social media network data usage policies is rather clear and concise. Policies across Facebook, Twitter and LinkedIn have been well organized and structured in a manner which are easy to read. Internet Society’s Global Internet User Survey reports that only 16% of Internet users review these policies and even worse, only 20% of those that do, understand its contents.  However, if they are to read them, it would likely occur at the sign up stage.4 Having signed up for each service anew there are certain transparency issues which arise quickly. When signing up for a new Facebook account, the privacy policy link was so small in comparison to the “Create Account” call to action that I overlooked it altogether. Twitter slightly improves on this user interface by allowing potential users to read the entire policy directly on the page, albeit in very small font. Lastly, LinkedIn applies a similar sign up strategy to Facebook. ! 3 “The Age of Predictive Analytics: From Patterns to Predictions, Office of the Privacy3 Commissioner of Canada, August 2012 Lifehacker, http://lifehacker.com/5964185/do-you-read-privacy-policies-and-do-you-4 understand-them
  • 4. It is worth distinguishing LinkedIn from Facebook and Twitter when evaluating these privacy policy pages. At nearly 8,000 words, it is not the longest, however the network has taken great care in marketing their “trust” policy. Employing icons, embedding a video and sectioning of the content adds a sense of approachability to the document. After thorough review of the text, three transparency issues arise. They are as follows  :5 ! 1. LinkedIn states that user information may be shared with “LinkedIn affiliates” but does not identify the full list of affiliates or how they would, in fact, be using the user data in detail. ! 2. When addressing data sharing with “Third Parties,” the language used to describe these regulations changes from a casual business tone to legal and technical jargon. ! 3. The nearly 2-minute long privacy policy video found at top of the page, which is intended to save users time by skipping the fine print, only touches upon some of the most sensitive areas of the document and skips most sections of the policy. ! The second and third points illustrate Helen Nissenbaum’s Transparency Paradox. As she explains, if the policy “finely details every flow, condition, qualification, and exception, we know that it is unlikely to be understood, let alone read. But summarizing practices in the style of say, nutrition labels is no more helpful because it drains away important details, ones that are likely to make a difference.” 6 While all three social networks originally began harvesting user data to drive ad sales, as each network introduced new revenue streams, more and more of data was 4 LinkedIn Privacy Policy, http://www.linkedin.com/legal/privacy-policy.5 Nissenbaum, Helen. “ A Contextual Approach to Privacy Online,” http://www.amacad.org/6 publications/daedalus/11_fall_nissenbaum.pdf, pg 36.
  • 5. being analyzed in much more sophisticated ways. These adjustments have forced social networks to alter their policies on an on-going basis. LinkedIn for examples, now has three main streams of revenue: premium accounts, ad sales — which most users are aware of — and what Financial Review calls its “gold mine”: “a suite of products created by its token solutions division and sold to corporate clients.”  This third stream returned $205 million dollars (US) in revenue during the7 second quarter alone of 2013. While LinkedIn’s privacy policy is clear about advertising data use, it does not explicitly state how its data collection contributes to the company’s “gold mine.” ! Why Is Transparency Important? ! Furor recently erupted when it was revealed that Facebook performed a psychological experiment on approximately 700,000 of its users, unknowingly and without receiving consent  . Aimed at gaging the emotional state of its users, the social8 network tested whether a decrease of negative or positive posts would effect the type of status updates generated by users. Given the intense backlash reported in the media  , it is safe to say that most users9 were not aware their activity was being monitored for network experiments. An ethics issue clearly arises here for Facebook, but more importantly (in the context of this paper), its transparency measure are put into question by its users, the media and business partners. Many users and even governments questioned the legality of the experiment and declared it unethical at its core. ! 5 Financial Review. “How LinkedIn’s using your data” http://www.afr.com/p/national/work_space/7 how_linkedin_using_your_data_G0CiiqJ3feJ4SmbTnOR7lK Wall Street Journal. “Furor Erupts Over Facebook's Experiment on Users” http://8 online.wsj.com/articles/furor-erupts-over-facebook-experiment-on-users-1404085840 Wall Street Journal. “Furor Erupts Over Facebook's Experiment on Users” http://9 online.wsj.com/articles/furor-erupts-over-facebook-experiment-on-users-1404085840
  • 6. What is even more demoralizing is that Facebook’s privacy policy at the time (2012), did not express this type of data manipulation to its users — explicitly or implicitly: ! “Four months after this study happened, in May 2012, Facebook made changes to its data use policy, and that’s when it introduced this line about how it might use your information: “For internal operations, including troubleshooting, data analysis, testing, research and service improvement.”  10 ! Today, Facebook’s privacy policy includes the “research” declaration but does not make explicitly clear the potential of data manipulation for experiments, let alone psychological one. “We may use the information we receive about you for internal operations, including troubleshooting, data analysis, testing, research and service improvement,”  the policy reads.11 The controversy created from this substantial lack of transparency mirrors itself on a smaller scale for Twitter and LinkedIn. In 2013, Twitter’s Transparency Report 12 revealed that the U.S. government completes 80% of info requests, and in 2011, LinkedIn received backlash from its users who discovered their profile image being used in the networks ads without consent  . Both events generated considerable backlash.13 The result which can be drawn from these public relations nightmares is twofold. Firstly, the data usage policies of social media networks do not offer users enough transparency. The backlash reported online indicates users are not aware of the extent of 6 forbes.com, “Facebook Added 'Research' To User Agreement 4 Months After Emotion10 Manipulation Study” http://www.forbes.com/sites/kashmirhill/2014/06/30/facebook-only-got- permission-to-do-research-on-users-after-emotion-manipulation-study/ Facebook Privacy Policy, https://www.facebook.com/about/privacy/your-info11 Twitter Transparency Report, https://transparency.twitter.com/12 Gadgetwise Blog, New York Times. “LinkedIn’s Social-Ad Misstep” http://13 gadgetwise.blogs.nytimes.com/2011/08/17/linkedins-social-ad-misstep/? _php=true&_type=blogs&_r=0
  • 7. data manipulation which occurs. Secondly, transparency is important and highly valued to Facebook, Twitter and LinkedIn users. ! Solutions & The Future of Social Network Transparency ! Many approaches can be taken to rectify social media’s lack of transparency. The first, and rather simple, approach is to increase the privacy policy’s visibility on each network. Rather than placing the document link in the footer, or in small font, force the user to opt-in through interactive measures. Secondly, I propose to educate the user on the end product of data manipulation, not necessarily the process. While I do agree with the Office of the Privacy Commissioner of Canada when it states, “the complex processes that underlie predictive analytics or data mining techniques are usually quite lost on many individual, if not most,”  the14 exact type of information which is derived from it could be easily and clearly communicated to the user. Lastly, users should be given the choice to control what type of information is used for data manipulation. Allowing the ability to customize a policy introduces the element of choice, which I believe would entice users to become more involved in the process of privacy. This final approach, however, will impact the pool of data collected by social networks, and most likely in a negative way. Ultimately, I believe the user must be made aware of the value that his or her data generates. Beyond its issues concerning privacy and transparency, what does the future of Data look like? One last issue that arises from this discussion is the question of asymmetric information flow: is the final exchange between free social networks and users, a fair one? Companies such as New York-based startup Datacoup  are likely to15 grow as users become more aware of their data’s tremendous value. Though the service 7 “The Age of Predictive Analytics: From Patterns to Predictions, Office of the Privacy14 Commissioner of Canada, August 2012 datacoup.com15
  • 8. does not address issues of privacy — in fact, it may even worsen the issues at hand — it is dubbed as the “first personal data marketplace.” The platform allows consumers to “aggregate and sell” their anonymous personal data for $8 per month  .16 Although talk of selling your data online has been in talks for some time now, the idea has yet to be embraced by both consumers and retailers, who would greatly benefit from the insights of combined spending and online activity. Datacoup CEO and cofounder Matt Hogan touts the service as revolutionary because “few data providers can combine traces of a person’s online activity with a record of their spending activity.” The combination of data is said to “unlock more value, and there’s no way to do that other than from the user themselves.” ! ——————————————————- ! In conclusion, the usage of large social media networks combined with a lack of transparency measures creates three major problems: users are unaware of the type of data that is collected and being shared, how it’s being used and what results are derived from it. By examining Facebook’s Emotion Manipulation Study and similar situations at Twitter and LinkedIn, it is clear that transparency on social media networks must improve. It was concluded that transparency is important to users and, therefore, it is in the social network’s best interest as a service providers to offer a highly-valued, ethical and transparent experience to its users if they wish to continue their ongoing growth. 8 datacoup.com16