Data Mining and its Role in Privacy

This article discusses the role of data mining in compromising privacy and its ethical implications. It explores how social media uses data mining techniques to manipulate user behavior and compromise their privacy.

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Contents
Data mining role in privacy.............................................................................................................1
Effects for individuals and society..................................................................................................2
Ethical implications of these data mining practices........................................................................3
References........................................................................................................................................5

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Data mining role in privacy
Data mining is beneficial for business purposes and it is useful to enhance business of an
organization. It has large volume of information to analyses different things, such as behaviour
of customers, and many others. According to ( Guru-Murthy, 2018), Jaron Lanier said that social
media is ruining social life of people and it manipulated behaviour of their users. Social media
makes their users addictive for their products and services.in addition, they uses data mining
techniques to compromises their privacy.
Social media uses data warehouses for storing their users and business information. It is a
way to store large amount of data for further use, which is used to decision making. Facebook,
Google, twitter, and many other social media used a business model, which makes their users
addictive and change their behaviour using internet algorithms. Those internet algorithms
searches in data warehouses and found the proper data set to manipulate the user for their
business purpose. It has already happened with Facebook that they share person information of
their users for research, but it is used for different purpose, as an example Cambridge Analytica
case (IAME, 2018).
Many data mining techniques are used to identify user behavior and based on that
analysis social media provide them related things, which makes them addictive ( Brown, 2012).
It is not good from privacy point of view. It reduces security and privacy of personal data, such
as email, password, phone number, address, and many others.
Data mining techniques are used to found out behaviour of users of social media
according to their business model, which makes them addictive for their services. They are
playing with their personal information though internet algorithms. Data mining is used to
enhance business performance but it is used for making users addictive and makes a business
form social media (Larose & Larose, 2014).
Facebook is highly used social media in young generation and it will affect their social
life, as they are having online friends only. They are addictive and change their behaviour
according to the suggestions and new applications of social media.

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Effects for individuals and society
It effects on individual and society in terms of addictiveness of the social media. Most of
the people are present in any social media as per their connivance. In addition, according to Peter
Eckersley, Facebook can learn almost anything about a person using artificial intelligence and
machine learning algorithms to analyze behavior of a person ( Singer, 2018).
Artificial intelligence is having many algorithms, which can provide information about a
person behavior from their social media information in data warehouses using deep learning.
According to many surveys and feedbacks that organizations are uses personal information of
their customers, such as user’s behaviour. They use their preferences from database and provide
those related services and offers. Business Intelligence (BI) is a solid example of this thing
(Vercellis, 2011).
According to the ( Singer, 2018), 87 million Facebook users data is used by Cambridge
Analytica for voter profiling in US election. Facebook is collecting user’s information from not
only Facebook; they also get information from non-Facebook sites all over the web. Facebook
uses different software tools to track user’s activities. It uses like and share button to get
information and behavior of users. Therefore, they can provide related advertisements and post
to them. It makes them more addictive for those things.
In addition, Facebook can access the information from different sources on the web about
the users. It can access many portals, which are providing access to them. It makes many effects
the personal and social life of users, as they are highly addicted for social media and lost their lot
of time on it. From privacy point of view, Facebook’s data warehouse is having all the
information of billions of users.
Personal life depends on the society and now a day’s social life is only on the internet. It
was a worst thing that a person is having their friends on web only. All the things are depends on
the behavior of a person and social media is manipulating behaviour of a person using their
personal information.

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Ethical implications of these data mining practices
Data mining can be providing a security to the customers and business information of an
organization through its security policies and encryption technologies (Abbas, 2005). There are
many things to be used for business purpose. Data mining can be used for many purposes in
business model, such as suggestion for games and other actives.
In terms of ethical point of view, data mining practices are used to identify the behaviour
of a person nut it cannot use for business purpose. Artificial intelligence has many algorithms,
which can provide almost every information about a person behaviour based on their social
media and other data and information on the web (Liao, Chu, & Hsiao, 2012).
Social media is created for the connectivity but it is used to make a business from that
entire user’s personal information (Olson & Delen, 2008).
According to (Shmueli, Bruce, Yahav, Patel, & Lichtendahl Jr., 2017), data mining will
be used for business analytics, but it uses for manipulating behaviour of users through knowing
about their behavior using data mining practices, such as internet algorithms. It is away to
identify behaviour of a user.
Facebook is already having a bad experience as they provide data for research purpose
but it used for personal benefits. They are only responsible for that Cambridge Analytica scandal
and they should learn from that incident that it is not ethical to use personal information of their
users without any prior information of all those users (Bloomberg, 2018).
According to (Confessore, 2018), Facebook is having responsibility of privacy and
security of personal information of their users. They have all security features in their system and
business model. However, data breaches have happened in a high ratio in present era. Therefore,
privacy and security is necessary, if any organization is having information of a user in their
databases. Most of the organisations are having their customer data in their CRM and it is
connected with the Internet. Moreover, they are not having security policies and standards to
secure customers and business information.
Social media is having all the rights to take personal data of the user but they cannot
share user’s personal information to anyone for their personal benefits. According to laws, it is

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not legal to share personal information to anyone without permission of concern person. Social
media is beneficial but it ruined social life of present generation as well as they are playing with
the personal information of users, which is not ethically right. Government is highly considering
this situation and provides security policies about the customer’s information and it is a
responsibility of the organization to provide privacy and security to the personal information of
customers as well as business data.
Data mining and BI are used to optimization and it used for decision-making. Decision
support system and business intelligence system are interrelated to each other. BI and DW are
considered in a business market strategy to get more growth. DW provides tools and technology
for business intelligence. It will provide many benefits in terms of performance and productivity.
BI provides user support, which is a better way to maintain their customers. BI tools and
applications are highly used in business and it uses data of customer relationship management
(CRM) system (Obeidat, North, Richardson, & Rattanak, 2015).

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References
Brown, M. (2012, December 11). Data mining techniques. Retrieved from IBM:
https://www.ibm.com/developerworks/library/ba-data-mining-techniques/index.html
Guru-Murthy, K. (2018, June 15). Jaron Lanier interview on how social media ruins your life.
Retrieved from Channel4: https://www.channel4.com/news/jaron-lanier-interview-on-
how-social-media-ruins-your-life
Singer, N. (2018, April 11). What You Don’t Know About How Facebook Uses Your Data.
Retrieved from nytimes: https://www.nytimes.com/2018/04/11/technology/facebook-
privacy-hearings.html
Abbas, O. (2005). The Role of Data Mining in Information Security. Retrieved from
www.researchgate.net: https://www.researchgate.net/figure/Data-mining-
Process_fig2_295907254
Bloomberg. (2018). Facebook Cambridge Analytica Scandal: 10 Questions Answered. Retrieved
09 05, 2018, from http://fortune.com/2018/04/10/facebook-cambridge-analytica-what-
happened/
Confessore, N. (2018). Cambridge Analytica and Facebook: The Scandal and the Fallout So
Far. Retrieved September 21, 2018, from
https://www.nytimes.com/2018/04/04/us/politics/cambridge-analytica-scandal-
fallout.html
IAME. (2018, March 19). The Facebook Data Mining Scandal — What happened. Retrieved
from medium.com: https://medium.com/@IAMEIdentity/the-facebook-data-mining-
scandal-what-happened-82154855aeca
Larose, D. T., & Larose, C. (2014). Discovering knowledge in data: an introduction to data
mining. New Jersy: John Wiley & Sons.
Liao, S.-H., Chu, P. H., & Hsiao, P. Y. (2012). Data mining techniques and applications–A
decade review from 2000 to 2011. Expert systems with applications, 39(12), 11303-

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11311.
Obeidat, M., North, M., Richardson, R., & Rattanak, I. (2015). Business intelligence technology,
applications, and trends. International Management Review, 11(2), 47-56.
Olson, D., & Delen, D. (2008). Advanced data mining techniques. Berlin, Germany: Springer
Science & Business Media.
Shmueli, G., Bruce, P., Yahav, I., Patel, N., & Lichtendahl Jr., K. (2017). Data mining for
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& Sons.
Vercellis, C. (2011). Business intelligence: data mining and optimization for decision making.
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