How Facebook Uses Big Data To Increase Its Reach

Summary: Facebook’s massive user base generates a mountain of data on their preferences and habits. This “big data” is analyzed to understand users and deliver highly targeted advertising.  By showing relevant ads, Facebook keeps users engaged and advertisers happy. This personalized approach fuels Facebook’s growth, making it a dominant platform for digital marketing.

Data, Analytics, AI, and robotics, today, the tech discussions revolve around these topics. With the significant development technology has made in our life, it has also brought forth some interesting insights. One of them is the large volume of data that we are creating every day. Facebook, which brought the social media revolution, generates around 500+ terabytes of information every day. All these pieces of information hold great significance. But deploying conventional methods to extract insight from this data is not feasible. Here comes the role of Big Data.

The Symbiotic Relationship Between Facebook and Big Data

Facebook has been leveraging Big Data technology to extract meaningful insights. Every activity of the Facebook user, like the active hours on Facebook, photos, videos, liked photos, games that you play, and posts liked etc. All this information is collected by Facebook, assessed and analysed. Based on this, Facebook is able to make personalised recommendations. With every passing second, new data is being fed into the system.

Quick Snap at Mounds of Data Being Fed in Facebook

  • Every 60 seconds, Facebook users upload around 136,000 photos
  • The comment section is busted 510,000 comments every minute
  • And 293,000 status updates are posted on Facebook every 60 seconds
  • Every day, Facebook generates 500 + terabytes of information.

So, what happens with this information? What is the relevance of this data for Facebook? In this blog, we are going to focus on the usability of this data. Also, we will be highlighting how Facebook is using this data to enhance customer experience.

How Does Facebook Use This Data?

How Facebook Uses Big Data

As we have mentioned in the beginning, the data present on Facebook is pivotal. Facebook analyzes your data (likes, clicks, habits) to show you targeted ads and suggest relevant content and friends. This personalized experience keeps you engaged, which fuels Facebook’s reach and influence. It helps in the following:

Personalized Advertising

This is a major application. Facebook analyzes your likes, shares, clicks, browsing habits (including those outside Facebook with tracking cookies), and even things like how long you hover over content. Using complex algorithms, it builds a profile of your interests and shows you advertisements highly likely to resonate with you. This keeps users engaged with relevant content and makes advertising more effective, leading to more revenue for Facebook. 

Content Recommendations

Facebook analyzes your activity to suggest friends, groups, and even upcoming events you might be interested in. This creates a personalized user experience that keeps you coming back for more, increasing engagement and time spent on the platform.

Improved Features

Facebook uses data to constantly refine its features. For instance, facial recognition technology helps suggest who to tag in photos, while data on user behavior helps optimize the News Feed algorithm to show you the most interesting stories.

Security and Safety

By analyzing user activity, Facebook can identify and flag suspicious behavior that might indicate spam, fake accounts, or even threats. This helps maintain a safer and more trustworthy environment for users.

Ways Facebook is Using Big Data

Facebook goes beyond social. They analyze your data to target ads, personalize your newsfeed, improve features, and even fight spam for a safer platform, all to keep you engaged.

Analysis of Text

You would agree that a large volume of data is added to Facebook. With DeepText, Facebook tries to extract the meaning of the words added to the posts.

Facial Recognition

With the DeepFace technology, Facebook analyses the image and, based on it, recommends the name of the friends for tagging. This technology also assesses whether the two different images are the same or not.

Targeted Advertising

Advertising is one of the areas where Facebook uses Big Data technology to promote several businesses. However, it is a great tool for promotion and branding but is also controversial because it tracks the user’s activity.

Analysing Likes

Facebook analyses the activities of the user. Assessing the likes helps Facebook predict the intelligence, emotional stability and religious sentiments of the people.

Leveraging the Benefits of Big Data: The Facebook Way

Facebook uses Big Data in a number of ways, from providing you the right information and connecting you with your peers, it also has added offerings to make. The following is the illustration of how Facebook is different from the others:

Takes You Down The Memory Lane: The Flashback videos

Facebook does take you back in time, well, not literally, but yes, the replay of the good old memories definitely brings back a smile on the face. On its 10th anniversary, Facebook presented the option of viewing and sharing videos from the date of registration till the present time. This compilation takes into account photos and posts that have maximum comments or likes. Facebook combines everything in the form of video backed by a piece of nostalgic background music.

The Social Cause: “I Voted” Experiment

In 2010 Facebook launched a massive experience wherein it generated an I Voted sticker. The user could add the I Voted sticker to their profile. This also motivated individuals to cast their votes. As per the claims of Facebook, because of peer pressure, around 340,000 more people cast their votes in the 2010 midterm elections.

The Tagging Game: Facial Recognition

We love to tag our friends on Facebook. It’s fun, but do you know what runs behind it? It’s actually Big Data technologies. Facebook adopted it to detect the details in specific pictures or videos, thus guiding the user to tag their friends.

For this, the Deep Learning application “DeepFace” is adopted. It trains the platform to detect people in the picture. Thus aiding the process of tagging. Additionally, Facebook has also claimed that its advanced image recognition tool in detecting the images of individuals.

Although it was a hit, but also garnered some raised eyebrows. Hence, Facebook made it an option to turn on and off the settings.

Some Concerns

Facebook collects vast amounts of user data, sparking concerns about privacy and control. Users worry about targeted ads, content manipulation, and potential misuse of their information.

Raises privacy concerns

The use of Big Data added some good credits to Facebook, but it raised some concerns regarding the privacy issue. Many users complained about the privacy settings. Some found it to be too complicated. Although Facebook had made several adjustments regarding the same, it didn’t quite go well with the users who were accustomed to the existing features of the platform.

Face Recognition Didn’t go Friendly

Although facial recognition was an innovative move by Facebook but also drew some concerns, the tool interpreted the pictures once it was uploaded, and the user got the liberty to choose whom they would want to tag. The technology supporting this feature matched the uploaded pic against the picture of the user’s friend on the list.

However, the controversy arose because the tool was powerful to detect the faces of different people, which is a hindrance to public privacy.

Empowering Connections: Big Data Analytics At Facebook

Big Data Analytics certainly plays an integral role in enhancing the customer experience. But at the same time, it also raises concern about the amount of tracking this app does. The Off Facebook Activity tracker introduced by Facebook leveraged the company to track all the activities of the user, like the website they were visiting, games played by them, apps they accessed by them and more.

Although there was a disabled tracking feature, to the dismay, the tool had access to recording everything the user was doing. Thus bringing the use of technology under the gauge.

In addition, Facebook also has a dedicated Data Science team that consistently keeps on posting updates on the insights they have gathered. It uses the user’s habit, thus helping them predict the user’s perspective and preference. Thus helping them understand the users.

 It eventually helps in promoting targeted advertisements. However, this is the tip of the iceberg. The burning question still exists: How will the company be using this data, and whether it can use this information to manipulate public opinion?

Conclusion

The massive application of Big Data by  Facebook is fascinating. But Facebook is not the only company that is leveraging the benefits of this technology. Platforms like LinkedIn, Twitter, Amazon, Google and many others for harvesting the benefit of data and realising the importance of Big Data for the benefit of their business.

This has also triggered the growth of this technology, thereby creating job opportunities for individuals excelling in this domain. If you two are interested in launching your career in the data domain, it’s time to connect with Pickl.AI.

We provide a comprehensive learning module that encompasses all the core technologies of Data Science and Big Data. Or online learning modules have been curated by industry experts. As a part of this learning module, you will also excel in using tools like Python, Matplotlib, NumPy, and others.

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Frequently Asked Questions

How Instagram Uses AI and Big Data?

Instagram also actively deploys technologies like AI and Big Data to provide a personalized experience to its users. It helps the user find the content they would want to explore more. Moreover, AI helps in sorting the feeds and posts they would want to know.

What Are the Challenges of Big Data?

Some of the key challenges of Big Data are:

Sharing of Data
Data Privacy
Quality of Data
The Selection of the Right Tool
Scalability

What are the 3Vs of Big Data?

The 3 Vs of Big Data are:

Volume– Amount of data that is being created

Variety- The different types of data.

Velocity- The speed at which the data is being created

Authors

  • I am a data enthusiast and aspiring leader in the analytics field, with a background in engineering and experience in Data Science. Passionate about using data to solve complex problems, I am dedicated to honing my skills and knowledge in this field to positively impact society. I am working as a Data Science intern with Pickl.ai, where I have explored the enormous potential of machine learning and artificial intelligence to provide solutions for businesses & learning.

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