The Dark Side of Social Media

Every like: tracked. Every post: saved. Every view: recorded. 

Deny it all you want, you likely do not understand how social media works. Once intended simply for reconnecting with friends, old and new, the role of social media has shifted to self expression, meeting new people, entertainment, support, learning, and even news coverage. Since 2002 and the start of the first proper social media platform, Friendster, the age of the average social media user has been decreasing. As of now, a majority of frequent social media users are teenagers. 70% of teenagers use Facebook, 51% of teenagers use Instagram, and 41% are on Snapchat. These users reap the short term benefits of social media but remain ignorant of the cost. As we swipe through our Instagram feeds, scroll through recommended videos on Youtube, and watch one minute documentaries on Snapchat, we only see the front end of the application. Even if you look at the source code of these applications, nothing seems secretive or illegal. However, the hidden and dark side of social media is the algorithm.

I know all of us have heard of the algorithm – a seemingly mystical entity that provides us with relief, entertainment, support, or (quite literally) whatever else we need to satisfy our digital craving. In order to understand what this algorithm truly is, we need to dive deeper into what makes social media so addicting (because admit it, unless you have some serious self-control, you often find yourself scrolling through random posts, tweets, or videos for hours upon end).

So why is social media so addictive? The Addiction Center classifies social media addiction as a behavioral addiction. Social media addiction might seem a little far from your habits. Maybe you are only on social media for a couple minutes a day. However, 10% of Americans have been classified with social media addiction while many more have never addressed or recorded this issue, due to ignorance of the situation. The attributes and patterns of social media addiction dangerously parallel those of substance use disorder. Substance use disorder, to put it simply, is drug abuse. 

Concerned yet? The similarity between drug use and social media use can be seen in favorable changes in emotional states (mood modification), salience (preoccupation with social media), tolerance (increasing use of social media over time), withdrawal symptoms (physical or emotional struggles if social media is restricted), and relapse (overuse after period of abstinence). Social media gives us surges of dopamine with every liked post, “snap back”, and retweet. According to addiction experts and doctors, social media has the same addictive qualities and symptoms as drugs. Now we know why social media is addicting – shots of dopamine and drug-like symptoms. However, what role does this algorithm play in the social media scheme?

An algorithm is defined as a process or set of rules to be followed in calculations or other problem solving operations, especially by a computer. Sounds like the constitution? In reality, the algorithm we are talking about does not function as a set of rules. Rather, it functions as a process, mapping out each of our views, clicks, posts, and likes in order to push favorable content our way. These algorithms are lines of code, jumbled in with all the other code that makes the app look and function properly. If you are well versed with the software side of technology, you will know that code isn’t one general language. In order to speak to the program and command it to do different actions, many different programming languages need to be used. To make a website, most web developers use HTML, CSS, JavaScript, PHP, Angular, NestJS, React, and other JavaScript frameworks. To create iOS applications, app developers use Swift, UI-kit, and other swift frameworks. To create and use an algorithm, similarly, the main languages used for machine learning processes are Python and R. 

Python has multiple frameworks that allow it to be used for a variety of purposes, including web development, video game development, graphics, data science, and machine learning. Algorithms are mainly used in the field of Data Science to collect, clean, analyze, and report patterns in data. Algorithms are powered by data – the more data you put in, the more accurate an algorithm is at predicting an outcome. Algorithms generally specialize in one narrow field. Whether it is predicting whether a patient has diabetes or not, to predicting the future price of a house based on economic and stylistic trends, one algorithm has a very narrow range of variability. The algorithm in this scenario, the social media algorithm, specializes in using our posts, comments, likes, searches, and viewership as data points to train and predict accurate results, mainly ads and sponsored content. 

Companies like Nike, Adidas, and Amazon advertise their products on the social media we use. Facebook, Instagram, and Snapchat may be free, but our attention is the product. There is a constant auction going on inside of the algorithm, selling our attention, the content we view on our screen, to the “highest bidder”. After using the data points collected and predicting what type of content will trigger the highest dopamine surge, the social media algorithm sells the adspace and video space on our screens to companies who advertise products similar to the content that triggers the surge. This gives companies a higher chance of increasing sales and social media companies more bidders and higher bids, all while our attention is being manipulated amidst our ignorance.

To get technical, there is an official term for the “social media algorithm”. Instagram, for example, uses a “mixed input neural network”, as do many other social media companies.  So what is a neural network? Well, neurology is the study of nerves, like the fibers in our body that transmit electrical signals. These nerves connect to create networks that can pass information and these networks power cognitive capabilities like common sense, reasoning, deduction, and more. The neural networks in algorithms are artificial neural networks; lines of code that evaluate data and send it to its corresponding node. Don’t worry if you’re confused; researches are working on understanding computational neural networks at this very moment. 

A mixed input neural network uses multiple randomized inputs to generate one output. These multiple inputs include all the data points we discussed, from how quickly you exit a video to what kind of posts you spent the most time on. After collecting these data points, the mixed input neural network decides what type of advertisements, videos, and topics the viewer is interested in and gives this data to the main source code of the application. The application then uses this data and the algorithm’s prediction to sell screen space to advertisers who are in the same categories you are interested in.

So what’s the big deal with that? Some people think that these personalized advertisement algorithms are a win-win; the viewer sees ads relevant to them while the companies advertising get increased interest in their information. However, it isn’t that simple. These advertisements are changing the way you view the world. 54% of teens use social media as a news outlet. Their Instagram feeds and suggested Snapchat Videos are being manipulated by corporations, artificial intelligence, and political organizations to provide a twisted view of current events. 

The bias of content on social media increases and creates severe partisan divisions amongst all social media users, including the younger generation. This polarizing effect was clearly demonstrated during the months leading up to the 2016 presidential election and, in similar fashion, is being repeated now. The majority of teens are viewing a world through a twisted, corrupted, and manipulative lens. Due to these immoral actions, the world is dividing, people are being manipulated into believing false information, the world’s greatest democracies crippling into autocratic dysfunctions, corporations are gaining money in the billions, all while the truth is burning.

What’s at stake when our attention is being sold to corporations? According to Jaron Lanier, a computer philosopher, the environment, politics, and the future of our civilization are at stake. By relying on social media, we may fail to rise up to the challenges that our society faces.

So what can you do? Don’t rely on social media as a news source or believe everything you see online. Support responsible journalism, have civil discourse to enhance your understanding, and do research from reliable resources before believing in something. The next time you pick up your phone to check social media, remember this: “If you are not paying for the product, you are the product.”


Editor at The City Voice | MIPA Honorable Mention Award Winner

Hi! My name is Vishnu Mano and I am an editor here at The City Voice. Apart from writing/editing articles, my hobbies include music, speech and debate, and coding.

Notify of
Inline Feedbacks
View all comments