Facebook uses extensive data mining techniques to gather and analyze user data: 1. Facebook tracks users across the web through cookies and can identify users through facial recognition in photos to learn more about users' interests, habits, and relationships. 2. Analyzing patterns in users' likes, posts, and comments allows Facebook to accurately predict personal attributes such as sexual orientation, political views, and life satisfaction. 3. Facebook suggests tags for photos using image processing and uses "flashbacks" and "friendiversary" videos created from users' past posts and likes to demonstrate its ability to analyze large datasets through techniques like Hadoop clusters.

1. RESEARCH ON HOW FACEBOOK INDUSTRY IS USING DATA MINING
BY
SHAFIU UMAR ABUBAKAR
shafiuumarabubakar@gmail.com

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INTRODUCTION
DATA MINING
Data mining is the process of discovering patterns in large data sets involving
methods at the intersection of machine learning, statistics, and database systems. Data
mining is an interdisciplinary subfield of computer science and statistics with an
overall goal to extract information (with intelligent methods) from a data set and
transform the information into a comprehensible structure for further use. Data mining
is the analysis step of the "knowledge discovery in databases" process or KDD. Aside
from the raw analysis step, it also involves database and data management aspects,
data pre-processing, model and inference considerations, interestingness metrics,
complexity considerations, post-processing of discovered structures, visualization, and
online updating.
SOME OF THE TECHNIQUES OF DATA MINING
1. CHARACTERIZATION: is used to generalize, summarize and possibly different
data characteristics.
2. CLASSIFICATION: Data classification is a process in which the given data is
classified into different classes according to a classification model.
3. REGRESSION: This process is similar to classification the major difference is that
the object to be predicted is continuous rather than discrete.
4. ASSOCIATION: In this process the association between the objects is found. It
discovers the association between various data bases and the association between
the attributes of single database.
5. CLUSTERING: Involves grouping of data into several new classes such that it
describes the data. It breaks large data set into smaller groups to make the
designing and implementation process to be simple. The task of clustering is to
maximize the similarity between the objects of classes and to reduce the similarity
between the classes.
6. CHANGE DETECTION: This method identifies the significant changes in the data
from the previously measured values.

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7. DEVIATION DETECTION: Deviation detection focuses on the major deviations
between the actual values of the objects and its expected values. This method finds
out the deviation according to the time as well the deviation among different
subsets of data.
8. LINK ANALYSIS: It traces the connections between the objects to develop models
based on the patterns in the relationships by applying graph theory techniques.
9. SEQUENTIAL PATTERN MINING: This method involves the discovery of the
frequently occurring patterns in the data. Social networks are important sources of
online interactions and contents sharing ,subjectivity , assessments , approaches,
evaluation , influences , observations, feelings, opinions and sentiments
expressions borne out in text, reviews, blogs, discussions, news, remarks,
reactions, or some other documents .

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FACEBOOK
Facebook, Inc. Is an American online social media and social networking service
company based in Menlo Park, California. It was founded by Mark Zuckerberg, then a
Harvard computer science student on February 4, 2004, in Cambridge, Massachusetts
along with fellow Harvard College students and roommates Eduardo Saverin, Andrew
McCollum, Dustin Moskovitz and Chris Hughes. It is considered one of the Big Four
technology companies along with Amazon, Apple, and Google.
The founders initially limited the website's membership to Harvard students and
subsequently Columbia, Stanford, and Yale students. Membership was eventually
expanded to the remaining Ivy League schools, MIT, and higher education institutions
in the Boston area, then various other universities, and lastly high school students.
Since 2006, anyone who claims to be at least 13 years old has been allowed to become
a registered user of Facebook, though this may vary depending on local laws. The
name comes from the face book directories often given to American university
students. Facebook held its initial public offering (IPO) in February 2012, valuing the
company at $104 billion, the largest valuation to date for a newly listed public
company. Facebook makes most of its revenue from advertisements that appear
onscreen and in users' News Feeds.
The Facebook service can be accessed from devices with Internet connectivity, such
as personal computers, tablets and smartphones. After registering, users can create
customized profile revealing information about themselves. They can post text, photos
and multimedia which is shared with any other users that have agreed to be their
"friend", or, with a different privacy setting, with any reader. Users can also use
various embedded apps, join common-interest groups, and receive notifications of
their friends' activities. Facebook claimed that had more than 2.3 billion monthly
active users as of December 2018. However, it faces a big problem of fake accounts. It
caught 3 billion fake accounts in the last quarter of 2018 and the first quarter of 2019.
Many critics questioned whether Facebook knows how many actual users it has.
Facebook is now one of the world's most valuable companies.

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HOW FACEBOOK IS USING DATA MINING
PREAMBLE: Data mining techniques play a fundamental role in extracting
correlation patterns between personality and variety of user‟s data captured from
multiple sources. Generally, two approaches were adopted for studying personality
traits of social network users. The first approach uses a variety of machine learning
algorithms to build models based on social network activities only. The second one
extends the personality-related features with linguistic cues (Mairesse et al. 2007;
Oberlander and Nowson 2006). Several classification and regression techniques were
used to build predictive personality models along the five personality dimensions
using the linguistic features of a dataset comprised of few thousand essays solicited
from introductory psychology students (Mairesse et al. 2007).
Social media accelerates innovation, drives cost savings, and strengthens brands
through mass collaboration. Across every industry, companies are using social media
platforms to market and hype up their services and products, along with monitoring
what the audience is saying about their brand.
Possibly Facebook is the world‟s most popular social media network with more
than two billion monthly active users worldwide, Facebook stores enormous amounts
of user data, making it a massive data wonderland. It‟s estimated that there are more
than 169 million Facebook users in the United States alone by 2018. Facebook is the
fifth most valuable public company in the world, with a market value of
approximately $321 billion.
Every day, we feed Facebook‟s data beast with mounds of information. Every 60
seconds, 136,000 photos are uploaded, 510,000 comments are posted, and 293,000
status updates are posted. That is a LOT of data. At first, this information may not
seem to mean very much. But with data like this, Facebook knows who our friends
are, what we look like, where we are, what we are doing, our likes, our dislikes, and
so much more. Some researchers even say Facebook has enough data to know us
better than our therapists!
Apart from Google, Facebook is probably the only company that possesses this
high level of detailed customer information. The more users who use Facebook, the
more information they amass. Heavily investing in their ability to collect, store, and
analyze data, Facebook does not stop there. Apart from analyzing user data, Facebook
has other ways of determining user behavior.

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SUMMARY OF HOW FACEBOOK IS USING DATA MINING
 TRACKING COOKIES: Facebook tracks its users across the web by using tracking
cookies. If a user is logged into Facebook and simultaneously browses other
websites, Facebook can track the sites they are visiting. This allows Facebook to
know more about the user‟s likes and dislikes.
 FACIAL RECOGNITION: One of Facebook‟s latest investments has been in facial
recognition and image processing capabilities. Facebook can track its users across
the internet and other Facebook profiles with image data provided through user
sharing.
 ANALYZING THE LIKES: A recent study conducted showed that is practicable to
predict data accurately on a range of personal attributes that are highly sensitive
just by analyzing a user‟s Facebook Likes. Work conducted by researchers at
Cambridge University and Microsoft Research show how the patterns of Facebook
Likes can very accurately predict your sexual orientation, satisfaction with life,
intelligence, emotional stability, religion, alcohol use and drug use, relationship
status, age, gender, race, and political views among many others.
 TAG SUGGESTIONS: Facebook suggests who to tag in user photos through image
processing and facial recognition. And this is typical use of data mining.
 USING BIG DATA: Videos on Facebook that shows a “flashback” of posts, likes,
or images, like the ones you might see on your birthday, or on the Friendversary
that is anniversary of becoming friends with someone is example of big data uses
by Facebook
Facebook Inc. analytics Chief Ken Rudin says, “Big Data is crucial to the
company‟s very being.” He goes on to say that, “Facebook relies on a massive
installation of Hadoop, a highly scalable open-source framework that uses clusters
of low-cost servers to solve problems. Facebook even designs its own hardware for
this purpose. Hadoop is just one of many Big Data technologies employed at
Facebook.”
 THE FLASHBACK: Honoring its 10th anniversary, Facebook offered its users the
option of viewing and sharing a video that traces the course of their social network
activity from the date of registration till the present. Called the “Flashback,”

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This video is a collection of photos and posts that received the most comments and
likes and set to nostalgic background music. Other videos have been created since
then, including those you can view and share to celebrate a “Friendversary,” the
anniversary of two people becoming friends on Facebook. You‟ll also be able to
see a special video on your birthday.
 TOPIC DATA: Is a Facebook technology that displays to marketers the responses
of the audience with regard to brands, events, activities, and subjects, in a way that
keeps their personal information private. Marketers use the information from topic
data to selectively change the way they market on the platform as well as other
channels.
 SELLING DATA TO MARKETERS: Facebook is a free social media; data is the
currency of free social media. Facebook sell the behavior that a user shares or
expresses to marketers. In 2016 around 98 data points are used to be sold to
interested companies such as user„s gender, age, political position, relationship
status and many more (Glum, 2018). Facebook also uses the user„s profile and
internet activity for advertisement purposes and it has generated profits at a rate of
about US$20.21 per user in 2017 (Glum, 2018).
 MARKETING AND ADVATISEMENT: Facebook provides users with a free social
networking site. In return, users can provide basic demographic information
through their likes, interests, and activities shared in their accounts. All of this
information is very valuable to marketers who want to pay Facebook to place their
ads on the target consumer„s accounts. Many companies/organizations even
individuals specifically advertisers uses Facebook services for their advantages.
Due to this massive gold mine of data, advertisers wait like hungry vultures. In
fact, the 2015 Social Media Marketing Industry Report stated that Facebook is the
No one 1 social platform for marketers.
 COLLECTING DATA: Everything a user does in Facebook is collected, processed
and shared to friends and user„s network. It is also shared to a certain level to
Facebook third-party partners, sometimes are taken advantage by them. This is
characteristic using of data mining. The reason why Facebook‟s marketing
solutions are so profitable is because of the size of the reach Facebook has on
personal data. Not only does Facebook collect data from their own social media
platform, but also across Instagram, Messenger, and WhatsApp, which are some of
the biggest social media platforms that are around today . Along with the data that
these platforms provide, Facebook also collects data from developers using the

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 Facebook Pixel (which is a code website. It collect data that help you track
conversation from Facebook ads, build targeted audiences for future ads, remarket
to people who have already taken some kind of action on your website). You place
on your on their website and the developers using the Facebook SDK in their app.
These two products provide Facebook with data that was previously unattainable
with their social media platforms. The Facebook SDK allows any app developer to
utilize the Facebook login system and ad delivery system, and in exchange,
Facebook gets to expand their scope on people‟s personal data. To put the power of
the Facebook Pixel and SDK in perspective, let‟s say a person was browsing an
online shopping website that was running the Facebook Pixel. The person winds up
looking at a specific product but does not end up buying the product. The
Facebook Pixel keeps track of this person‟s potential interest in buying the product
for later ad delivery. The person then goes on their phone to play a game that is
running the Facebook SDK. While playing their game, it is very likely that an ad
will appear showing the same product that this person was contemplating on
purchasing previously.

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How Facebook is extracting useful data by using data mining

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LITERATURE REVIEW
The society has benefited so much from the advances in information and
communications technologies. In the past, people need to visit libraries in best
universities or monasteries where precious manuscripts were hoarded (Hean, 2000).
The development of digital computers opens its way to networked communications
which has revolutionized information sharing. In 1969, the first computer-to-computer
link was established on ARPANET or the Advanced Research Projects Agency
Network.
Social media refers to websites and applications that are designed to allow people to
share content quickly, efficiently, and in real-time. Many people define social media
as apps on their smartphone or tablet, but the truth is, this communication tool started
with computers. Social media serves as a great location for data mining because there
is an immense quantity of data, a wide variety of structured and unstructured data, and
great speed at which new data is added. In an article in Yale Law, the writer describes
social media mining as a company or organization collecting data from a large amount
of social media users in order to draw conclusions about the populations of users
In this report, we describe and evaluate Facebook‟s revolutionary data mining
algorithms that allow advertisers to target consumers through location, demographics,
interests, behavior, and connections. In addition, we discuss how their use of data
mining gives them the power to sway and change people‟s opinions on companies and
political persons.
Facebook has become more powerful now more than ever. As it expands its
network, more and more information becomes available for the company to use for
various purposes for an improved experience of a Facebook user and benefit of the
company. The social capital to which people have invested in the social media
platform made it more difficult for people to quit. The review of the literature revealed
how Facebook is using data mining and making reports from that. It is however very
evident that even if people who are aware of the risks involved still patronize
Facebook. Some may have tinkered with their privacy setting to improve privacy
control but their actions/activities on the net make that extra precaution useless. As the
internet becomes more of a necessity than choice, more and more information is
readily available for data mining through Facebook or other platforms capable of
phishing valuable information such as passwords.

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Facebook and Google are just two of many websites that keeps information about
the users. However, most of the user is not aware of the volume and value of
information they are providing. Ideally, software companies must share responsibility
about the products and services they offer in a manner that both helps protect
customers from potential harm (Kutterer, nd.).
PERSONALITY DATA: The study of personality reflected in user‟s Facebook
activities includes a wide range of features. Some of the most intuitively predicted
indices are the statistical data for user‟s activities (e.g., number of likes, statuses,
groups, tags, events). Demographic characteristics such as: age and gender, were
accounted for since their effect is known to manifest in the context under investigation
(Golbeck, Robles, and Turner 2011). Self-centered network parameters representing
the number of friends, and measures such as density, brokerage, and betweenness,
provide additional insight into user‟s social behavior instrumental in assessing
personality along several dimensions (Celli et al. 2013).
BASIC LINGUISTIC FEATURES: Several studies have pointed out to the significant
correlation between personality and the spoken or written linguistic cues (Pennebaker
and King 1999; Mairesse et al. 2007). A selected set of categories, which correspond
to the LIWC linguistic process variables (e.g., word count, words per sentence/status,
sentences per status, punctuation count and lexical diversity) have been accounted for.
In addition, a list of words related to online jargon, chat acronyms emoticons,
profanities, and slang words were included to account for the specific language use
exhibited by social network users.

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CONCLUSION AND RECOMMENDATION
 Social media data is clearly the largest, richest and most dynamic evidence base
of human behavior, bringing new opportunities to understand individuals,
groups and society. Innovative scientists and industry professionals are
increasingly finding novel ways of automatically collecting, combining and
analyzing this wealth of data.
 Possibly Facebook is the world‟s most popular social media network with more
than two billion monthly active users worldwide, Facebook stores enormous
amounts of user data, making it a massive data wonderland. And Facebook is
using data mining to extract useful data for advertisement, marketers, and ads.
 It is important that researchers have access to computational environments and
especially „big‟ social media data for experimentation. Otherwise,
computational social science could become the exclusive domain of major
companies, government agencies and a privileged set of academic researchers
presiding over private data from which they produce papers that cannot be
critiqued or replicated. Because, the biggest concern is that companies are
increasingly restricting access to their data to monetize their content.
 Facebook should have more data centers and at least one in each continents in
the world, so that they will improve the usage of data mining.

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