How Facebook is Using Big Data?
Last updated on 13th Oct 2020, Artciles, Blog
According to the current situation, we can strongly say that it is impossible to see a person without using social media. Because the world is getting drastic exponential growth digitally around every corner of the world. According to a report, from 2017 to 2019 the total number of social media users has increased from 2.46 to 2.77 billion.
People are using Facebook, Instagram, WhatsApp, and other social/Messaging mediums while doing their daily routines. So, this caused the average time spent on social media by an individual has been increased to 2 hours 22 minutes.
This drastic growth of social media is directly impacting the data generation. Yes, Whatever we do in social media including a like, share, retweet, comments and everything has been stored as a record, and which has been generated data.
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Some Interesting Statics Of Social Media
An article from Excelacom in 2016 about what happens on the internet in one minute? Let me give some bits from that :
In one minute..
- 700,000 logins on facebook
- Around 530,000 photos are shared on snap chat
- Around 350000 tweets are tweeted on twitter
- 30,000 photos are shared on Instagram
- 21 million messages on WhatsApp
In 2012, Facebook revealed that it is generating around 500+ terabytes of data every day. In which 2.7 billion were likes and around 300 million photos per day. Another exciting thing is Facebook is scanning around 105 terabytes of data per each half an hour.
Facebook has recently launched SIX Data centers around the globe to handle its immutable data efficiently.
For a user, all these information are just statistics, but for a business like facebook, these are all very big challenges. Because this data is not gonna dry, but sure it will increase rapidly. If they refused to handle all this data, sure their business would die of data overflow.
So what kind of strategy that businesses like Facebook have decided to handle all this data?
To handle all this data, Organizations like Facebook have adopted BIG DATA technology. Here we’re gonna discuss how Facebook is using big data analytics? Why they are using big data analytics. Let’s discuss more
How Big Data is Used on Facebook?
The main business strategy of Facebook is to understand who their users are, by understanding their user’s behaviors, interests, and their geographic locations, facebook shows customized ads on their user’s timeline. How is it possible?
There are around a billion levels of unstructured data that has been generated every day, which contains images, text, video, and everything. With the help of Deep Learning Methodology ( AI), Facebook brings structure for unstructured data.
A deep learning analysis tool can learn to recognize the images which contain pizza, without actually telling how a pizza would look like?. This can be done by analyzing the context of the large images that contain pizza. By recognizing the similar images the deep learning tool will segregate the images that contain pizza. This is how data Facebook is bringing a structure to the unstructured data.
In Deep Learning There are several use cases.
Textual Analysis
Facebook uses DeepText to analyze the text data and extract the exact meaning from the contextual analysis. This is semi-unsupervised learning, this tool won’t need a dictionary or and don’t want to explain the meaning of every word. Instead, it focused on how words are used.
Facial Recognition
The Tool used for this is DL Application, that is DeepFace which will learn itself by recognizing people’s faces in photos. That’s why we’re getting the name of the friends while tagging them in a post. This is an advanced image recognition tool because it will recognize if a person who is in two different photos is the same or not.
Target Advertisements
Facebook uses deep neural networks to decide how to target an audience while advertising ads. This Artificial intelligence can learn itself to find as much as can about the audience, and cluster them to serve them ads in a most insightful way. Because of this serving the highly targeted advertising, Facebook has become the toughest competitor for the ever known search engine Google.
Likewise, Behind the Facebook business model, there are a lot of interesting data handling methodologies, and there are a lot of controversial things behind facebook business flow. But, we don’t want to focus on those things.
How Data Science benefits Facebook
Facebook uses data science in the following 3 ways:
1. Textual Analysis
A large portion of data that is shared on Facebook is text. Facebook uses a tool it developed on its own called DeepText to extract meaning from words we write or post by learning to analyze them.
2. Facial Recognition
One of Facebook’s most recent 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 users by sharing in their profiles. It uses an application called DeepFace to teach itself to recognize photos of people. It says that this is the most advanced face recognition tool which is more successful than humans in recognizing two different images of the same person.
3. Targeted Advertising
Facebook uses data science to decide which advertisements to show to which users. Do you ever see sponsored ads on your feed while using Facebook? That’s targeted advertising and I know for sure this happens to you! If you don’t believe us, try searching the internet for something you have never searched for before. Then, log into Facebook and look at the advertisements that pop up for you. Are they similar to what you searched for? The answer is probably yes.
Here are some real-life examples that show how Facebook uses data science:
1. The Flashback
On celebrating its 10th anniversary, Facebook offered its users to view and share their anniversary of being friends with people on Facebook by making a video of photos and posts shared by them. These were the photos and posts that received the most number of likes and comments on the feed.
2. Celebrate Pride
In order to celebrate pride, Facebook introduced rainbow reaction, a way to support the Supreme Court’s judgment for marriage equality. It provided an easy, simple way to transform profile pictures into rainbow-colored ones.
3 million people on Facebook updated their profile pictures to the logo of the Human Rights Campaign.
Are you amazed to look at how cleverly Facebook uses data science as its weapon to effectively use its data and provide a better experience to its users?
Now you might think, what kind of information of its users is collected by Facebook?
1. Things you do and the information you provide:
It collects and stores your content and other information that you provide. For example – your personal details when you sign up, relatives, relationship status, phone number, likes and dislikes, etc.
2. Things others do and the information they provide to Facebook:
It collects information that other people such as your friends and family members provide about you, like when they share a photo of you, with you or send a message to you.
3. Your connections and networks on Facebook:
It collects information about the people and groups you are connected to and how often you interact with them, such as the people you communicate with the most or the groups you like to share with.
4. Financial information when you purchase on Facebook:
If you use Facebook for any kind of financial transactions like, when you buy something on Facebook, make a purchase in a game, it collects information about that purchase or transaction. This can be related to information about your credit card or debit card number, contact details, etc.
5. Information about how you access Facebook:
It collects information about the computers, phones, or other devices where you install or access its services such as device locations, the name of your mobile operator or ISP, browser type, mobile phone number, IP address, etc.
This is all possible because of data science and machine learning. These technologies play a big role in contributing to the success of companies and helping them to provide unbelievable features to their users.
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