How Facebook is Using Big Data - The Good, the Bad, and the Ugly
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.
The convergence of social media and big data gives birth to
a whole new level of technology.
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The Facebook Context
Arguably 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 will be more than 183 million Facebook users in the United States alone
by October 2019. Facebook is still under the top 100 public companies in the
world, with a market value of approximately $475 billion.
Social platform Prefernce
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 its
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.
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.
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.
Tag suggestions: Facebook suggests who to tag in user photos
through image processing and facial recognition.
Analyzing the Likes: A recent study conducted showed that it
is viable 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 shows 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.
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 hardware for this purpose. Hadoop is just one of many Big Data technologies
employed at Facebook.”
Example 1: 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 until the present. Called
the “Flashback,” 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 in celebrating a “Friendversary,” the anniversary of two
people becoming friends on Facebook. You’ll also be able to see a special video
on your birthday.
Example 2: I Voted
Facebook successfully tied the political activity to user
engagement when they came out with a social experiment by creating a sticker
allowing its users to declare “I Voted” on their profiles.
This experiment ran during the 2010 midterm elections and seemed
useful. Users who noticed the button were likely to vote and be vocal about the
behavior of voting once they saw their friends were participating in it. Out of
a total of 61 million users, then, 20% of the users who saw their friends
voting, also clicked the sticker.
The Data science unit at Facebook has claimed that with the
combination of their stickers that motivated close to 60,000 voters directly,
and the social contagion, which prompted 280,000 connected users to vote for a
total of 340,000 additional voters in the midterm elections.
Also Read: How Applications of Big Data Drive Industries
Example 3: Celebrate Pride
Following the Supreme Court’s judgment on same-sex marriage
as a Constitutional right, Facebook turned into a drenched rainbow spectacle
called “Celebrate Pride,” a way of showing support for marriage equality.
Facebook provided an easy, simple way to transform profile pictures into
rainbow-colored ones. Celebrations such as these hadn’t been seen since 2013
when 3 million people updated their profile pictures to the red equals sign
(the logo of the Human Rights Campaign).
Within the first few hours of availability, more than a
million users had changed their profile pictures, according to the spokesperson
for Facebook, William Nevius. All this excitement also raised questions about
what kind of research Facebook was conducting after their tracking user moods
and citing behavior research. When the company published a paper, The Diffusion
of Support in an Online Social Movement, two data scientists at Facebook had
analyzed the factors which predicted the support for marriage equality on
Facebook. Factors that contributed to a user changing profile pictures to the
red sign were looked at.
Example 4: Topic Data
Topic Data is a Facebook technology that displays to
marketers the responses of the audience about 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.
This data was previously available through third parties but
was not as useful because the sample size was too small to be significant, and
the determination of demographics was almost impossible. With Topic Data,
Facebook has grouped the data and stripped personal information for user
activity to help marketers by offering insights on all the possible activities
related to a specific topic. This gives marketers an actionable and
comprehensive view of their audience for the first time.
Facebook has always assured its users that information is
shared only with their permission and anonymized when sold on to marketers.
However, issues still seem to crop up; there have always been high levels of
privacy concerns among Facebook users, who ask, “Is Privacy Dead?”. For
example, many users complain that Facebook’s privacy settings are not clearly
explained or too complicated. It is easy for users to share things
unintentionally.
Two Problems with Facebook:
Ken Rudin states that companies who rely on Big Data often
owe their frustration to two mistakes:
They rely too much on one technology, like Hadoop. Facebook
relies on a massive installation of Hadoop software, which is a highly scalable
open-source framework that uses bundles of low-cost servers to solve problems.
The company even designs its in-house hardware for this purpose. Mr. Rudin
says, “The analytic process at Facebook begins with a 300 petabyte data
analysis warehouse. To answer a specific query, data is often pulled out of the
warehouse and placed into a table so that it can be studied. The team also
built a search engine that indexes data in the warehouse. These are just some
of the many technologies that Facebook uses to manage and analyze information.”
Companies use big data to answer meaningless questions. Mr.
Rudin also says, “At Facebook, a meaningful question is defined as one that
leads to an answer that provides a basis for changing behavior. If you can’t
imagine how the answer to a question would lead you to change your business
practices, the question isn’t worth asking.”
Conclusion
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expert.[Source]-https://www.simplilearn.com/how-facebook-is-using-big-data-article?source=frs_category
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