How Facebook uses Big Data to enhance customer experience

We’ve all received those flashback video notifications from Facebook on occasions like birthdays or friendship anniversaries, right? These videos contain images, likes, or posts of some of our old memories on the platform, a sweet present to help us reminisce and recall our journey with a few of our loved ones. 

 

But sentiments aside, have you ever wondered how Facebook generates these videos and what weapon it leverages to do so? This is done through Big Data, which the platform adopts for enhancing its user experience.
 

 

Speaking of Big Data, learn what is Big Data analytics through this blog. 

 

The social network builds its corporate image through its people. The whole premise of Facebook is built on the idea that people can rekindle/ maintain connections with their friends, acquaintances, and individuals they might share connections with. But have you ever thought about the technologies driving the premise of the platform? 

 

Facebook actually depends on algorithms for detecting these connections and for choosing the kinds of posts that will be given prominence on the user’s newsfeed. In layman’s terms the platform derives the information it holds on each of its users in order to build connections that the user may be interested in with the purpose of publishing ads and for generating the display of information in accordance with every individual’s personal interests, for instance, the posts of the friends, the user interacts with most may lead the newsfeed.

 

 

Examples of Big Data Applications

 

Example 1:-In its nostalgic flashback videos

 

On the occasion of the platform’s 10th anniversary, Facebook had presented to its users the choice of viewing and sharing a video that unearths the path of their activity on the platform from the date of registration until the existing time. As mentioned above, termed as the “Flashback,” this video is basically a compilation of photos and posts that gained the maximum comments and likes, which are accompanied by nostalgic background music.

 

These videos are also presented to users on occasions like their “friendversary”, i.e the anniversary of the day they became friends on the platform or on the occasion of the user’s birthday.

 

You can also sneak a peek at our blog on What is Facebook’s Transcoder AI

 

Example 2:- In its “I Voted” social experiment

 

Around the end of 2010, Facebook conducted an extensive social experiment in which it generated a sticker that enabled its users to announce “I Voted” upon their profiles.  

 

This experiment was conducted amidst the 2010 midterm elections and had quite an effective outcome. Upon laying their eyes on the I voted sticker, the users had more chances of voting and also of being more expressive regarding their voting act, as they observe their friends indulging in the action. 

 

As claimed by the Facebook scientists, the sticker — and the peer pressure pertaining to it caused 340,000 more people to vote in the 2010 midterm elections. 

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Examples of Facebook’s application of Big Data

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Example 3: In Commemorating Pride

 

Back in 2015, when the US Supreme Court declared same-sex marriages legal, Facebook introduced a rainbow filter tool that allowed its users to use it to show support for marriage equality. 

 

By availing of the rainbow filter tool and selecting the option of using it as their profile picture, the existing profile picture of the user was uploaded with the rainbow filter.

 

Similar commemorations were also carried out in 2013 when around 3 million people had updated their profile pictures to the logo of the Human Rights Campaign - the red equals sign.

 

Example 4:- Facial recognition:

 

A few of the Big data technologies adopted by Facebook include image recognition,  – a technology that instructs machines on how to detect the details in a specific picture or video, by guiding it through various other images. This technology enables the platform to be able to place the people in the pictures prior to us typing in their names and tagging them. It also allows the users to gain more access to the pictures of objects or things they like in their newsfeeds, whenever any of their friends like or shares them. 

 

The Deep Learning application “DeepFace” is adopted for teaching the platform to detect people in pictures. The platform claims that its most advanced image recognition tool is more successful than humans in detecting if two different images are of the same person or not. 

 

Facebook adopted facial recognition in the US back in 2010 when it inadvertently tagged people in pictures through its tag suggestions tool.  The user's face gets scanned by the tool and then the tool offers suggestions on who it assumes the person could be.  

 

The tool proved controversial at the time, which has been elaborated in detail later.  While being offered the choice of switching it off, the users were not. Although users had the option to switch it off, they were not distinctly asked if they had wanted it activated.

 

From December 2017 onwards, the tool was rechristened as face recognition and the feature for switching it on and off became smoother for the users. 

 

Later in 2019, the feature was made opt-in by Facebook as an effort for the platform to be more privacy-oriented. 

 

 

Drawbacks of the application of Big Data

 

1. Raises privacy concerns

 

The adoption of big data by Facebook has raised many privacy issues that the users are infuriated over. For instance, many users complain that the privacy settings of the platform are complicated or not properly clarified which results in people sharing information which they didn’t intend to. While the platform has repeatedly attempted to adjust this, this has ended up with people getting muddled since many of them had grown accustomed to the existing features of the platform.   

 

 

2. Issues encountered over face recognition

 

The platform’s facial recognition tool has raised a plethora of doubts and concerns. In this tool, once a picture is uploaded, the user gets suggestions regarding the people they can tag in it. This tool is based on an interpretation of the picture’s data, which is compared against pictures of the people in the user’s Friends list.

 

The adoption of this technology has proven to be pretty controversial. Various privacy campaigners claim that the application exceeds its limits since, in the case of high-resolution pictures of a crowd, it permits Facebook to identify a lot of the faces which becomes a hindrance to the public’s privacy and freedom to be anonymous. 

 

Recently the platform had consented to pay $650 million for a long-lasting class-action lawsuit, regarding its adoption of facial recognition. This lawsuit is regarding the platform’s photo-tagging feature, for which it employs facial recognition software for identifying faces in the user’s photos. The state of Illinois has established a law opposing the businesses gathering biometric data without obtaining consent firsthand and the state claimed that Facebook didn’t obtain approval prior to allowing the new feature by default to all the Facebook users in the state owing to which it sued the company in 2015.

 

 

3. Big Data Analytics At Facebook

 

The manner in which the habits of the user are assessed has raised additional concerns. In January 2020, Facebook introduced its Off Facebook Activity tracker  The tool offers users an itemized list of the websites, apps, and real-life stores that the platform knows they visited and also gives them the option to disable the tracking. Through these latest assessing tools the platform records everything the user does from how long their cursor hovers over certain parts of a page to what websites they visit outside of the platform, which in turn is used for generating the appropriate algorithms to determine the kinds of adverts to show the users.

 

Facebook has its own Data Science team with its own page where they consistently post updates regarding the insights which they have gathered from assessing the habits of the million people browsing the site.

 

From predicting the intelligence of users, their perspective on political issues, or their emotional stability, big data has played an integral role in making the platform effectively understand their users. 

 

This is an effort to aid the platform in selling targeted advertisements, yet it, in turn, raises the dilemma of how the data can be used by the government for discovering the public views and manipulating them.

 

 

The Facebook Cambridge Analytica scandal

 

A prominent example of the Facebook data privacy scandal is the Facebook Cambridge Analytica scandal. The scandal is focused on the gathering of personal data of over 87 million people by Cambridge Analytica, a strategic communication firm.  The firm, alongside others, gained access to the personal information of Facebook users owing to a number of factors, which also included improper safeguards against companies who perform data harvesting, lack of oversight of the platform’s developers, and also owing to the users consenting to largely vague terms and conditions of the platform.  

 

Cambridge Analytics had been able to gain access to personal user data via a personality quiz application “thisisyourdigitallife”. The data gained through this app is effective for developing a "psychographic" user profile. By adding the application to our Facebook account for taking the quiz, the creator gains access to the profile information, user history, and also the friends which the user has on Facebook. This also incorporates the posts they liked, posts of the user and their friends on the platform. 

 

 

Conclusion

 

From our friends, our location, our looks, our occupation to our likes and dislikes, Facebook has a lookout for everything! The platform possesses a detailed and advanced level of data regarding its users. The more users that adopt Facebook, the more data is garnered by the platform. By being massively engaged in its capacity for collecting, storing, and interpreting data, the platform has placed Big Data at the heart of its operations.