ENCOUNTERING THE ALGORITHM
From Facebook, Instagram, YouTube, or TikTok, how is it that they know what we’re thinking about or what we like? Why is it that our recommendation page understands more about us than how much we think it does? This occurrence is part of what the internet calls the “algorithm”. Even so, what is this so-called “social media algorithm” and how does it know what we’re thinking about, what we want to see? Social media users will most often encounter a situation where they stumble across a post that similarly reflects the things that they may have recently been thinking about months, weeks, even minutes prior. This can happen to anyone, no matter the large difference in interests they have. If you seem to like something specific on the internet, then you can expect more content of the same thing to show up over and over. If you’re a user that loves the Animal Crossing game or the franchise in general, then it’s likely that your recommendation page is filled with nothing but Animal Crossing. Whether it be about the game, merchandise from either the company or from small businesses, or even users who also show interest in it, your social media knows what you like and it makes sure that you see more of it. However, this coincidental encounter isn’t from the works of what some may claim is part of the government or artificial intelligence recording users’ every movement through the internet. It’s the idea that the internet–more specifically, in this case, social media–is taking into account what the users interact with online and adjusting their content to be relevant to what it believes will pique their interest.
WHAT IS THE SOCIAL MEDIA ALGORITHM?
If the algorithm affects our online experience so much, then what is it and why is it so important to the world of the internet? Is there a real reason as to why we see what we see? The social media algorithm serves as a system where social media will sort content from what is believed to be of relevance to the user’s interest (Golino 2021). This will help to encourage engagement for the user and keep them online longer–which will be explained as to why this is beneficial for social media platforms later down the research. It happens all the time even if we’re not aware of it. Another situation for thought could be a user who has an interest in changing their diet. This user will go through the internet searching for ways to get started. They may scroll through various posts on Instagram that give tips on healthy meals, watch short videos on TikTok of workout routines that they can do, or search through Google to discover nearby gyms that they can go to. They don’t realize what the internet is now doing in order to adjust its content to fit their ‘wants and needs’. At this point, the system, or algorithm, is generating posts that it believes the individual will eventually be choosing to look at and like based on the interaction they initiate. It’s as though it is trying to predict the user’s next move. As Figueiredo and colleagues put it in their article, Social Media and Algorithms: Configurations of the Lifeworld Colonization by New Media, he inputs that “Social Media algorithms actually predict something for each person, as it is not a force of expression, or metaphor, but it is a power of right prediction and distribution of content or ads for the right person…” to ensure the individual will see what they want to see (31). And note, that this can happen across any platform. The social media algorithm is not based on random data that it configures itself and pushes out to users hoping it is up to par with their preferences, it takes into consideration what the user is choosing to see hence its ability to showcase what the users want to see. It’s not simply a coincidence that the internet just so happens to know what others are thinking about.
THE ROOT OF IT ALL
Since the algorithm takes into consideration what individuals interact with, then it’s important to understand where it stems from: the concept of choice and preference. What does it mean? According to Zinas and Jusan in their article, Housing Choice and Preference: Theory and Measurement, the concept of choice and preference stem from the idea that, “Every person lives and operates within the framework of choosing from alternatives of lives endeavors…” (283). The outcome of an individual’s choice is based on the value and goal that is obtainable from the options they are given. When given the option between chocolate or vanilla, which would you choose? How about a pen or a pencil? Is there a certain brand that you prefer? How long have you known about the product? Is it something you’re interested in or already use? These are some concepts that the algorithm takes into consideration as it analyzes the stream of data that is being collected right from your account. One thing to note, however, is that choice and preference are two different items that fall under concept. “Preference is a function of choice,” as put by Zinas. Although a user may prefer to look up stationary items from a one brand rather than another, it is still a choice that user had initiated because of the level of fondness they have towards that specific brand. This is what the algorithm looks for–because the user had chosen to interact with this type of content, it must mean they want more of it. For a further detailed comparison of the two different, yet similar, terms, Coolen and his colleagues describe it as, “Preference refers to the relative attractiveness of an option or an attribute level, while intended or actual choice reflects the relative strength of behavioral tendencies (217).
Why does the algorithm exist?
The concept of the social media algorithm was not only to satisfy a user’s online experience but as well as implement the idea of connectivity. Just like water pipes or electricity cables, the use of online media was a gateway for advanced communication in which it “opened up a myriad of possibilities for online connections” (Dijck 5). This was a great leap for individuals who utilized technologies such as the telephone or mail to connect with others. It was the need for connectedness, a feeling of belonging to or having an affinity with a particular person or group, that drove individuals to seek this new form of communication. It became an advantage for these large platforms and they designed their application, and system, around the works of connectivity and the social media algorithm. As Dijck also puts it, “connectivity quickly evolved into a valuable resource as engineers found a way to code information into algorithms that helped brand a particular form of online sociality…” (4). Users could connect with one another through the use of liked hashtags, liked posts, recommended posts, groups, accounts, and so forth. It’s the idea that the algorithm is helping form the spark that will help ignite a conversation with other users. It played a part in providing materials that users were able to share with others who shared a common interest.
THE DEMAND OF THE ALGORITHM & THE GOLDEN RULE OF THE ONLINE SOCIAL WORLD
The social media algorithm has now evolved to become a global market of user-generated content. As Krumm and colleagues define the term in their article, User-Generated Content, “user-generated content comes from regular people who voluntarily contribute data, information, or media that then appears before others in a useful or entertaining way” (10). It’s one of the many ways that the social media algorithm is able to push out content that is suitable for each of its unique users. TikTok, for example, is the world’s most recent upcoming popular platform known for its feature of the For You feed, advertised as an “endless stream of short videos that feel personalized just for you”. Its success streams from its user-generated content which is assisted by the supreme system of the algorithm. The video-sharing app considers three main factors to be the main fuel of its recommendation system. Of those two are user interaction and video information–the third being device and account settings. Not only do likes and comments feed the algorithm data of the specific user’s personal interest, but the TikTok app has also coded a measurer that considers the duration of how long they’ve spent on a video to help personalize content. It is able to measure the number of times the video has played from beginning to end, if less than a minute, or how much of the video was watched, if longer than a minute. The data is recorded and mixed all together in the platform’s system along with keywords or hashtags from the creator’s posts to help better find what suits its user’s taste in entertainment. YouTube is another platform that also uses the same format of TikTok’s algorithm to best keep its users entertained for a long amount of time, keeping the platform highly active with users glued to their screens. Users are mainly the reason that they see what they see on the internet and a variety of social media platforms took that finding into consideration mimicking it in their own algorithm system.
It was especially an important tool as many businesses around the world have come to make use of the resource; after all, these platforms are also businesses themselves, and money has to be made to keep the entire process going somehow. “It must be further kept in mind that social media platforms are actual businesses, which make part of their revenue from marketing” (Gonlino 2021). This source of revenue stems from users staying online and the interactions they make, whether it be liking, commenting, sharing, or watching content. Take Instagram as an example. The platform, widely known for being a marketplace for businesses to showcase their products, and of course being a social connector, uses the algorithm to help improve business presence and build brand personality. The best way to gain popularity is to “cheat” the algorithm–this means playing with hashtags, and keywords, following similar or popular accounts, or even sharing content across various platforms. It’s like the “Golden Rule” for starting a business online; make sure to know how to utilize the algorithm to the best of its ability to be successful. Platforms themselves also use the algorithm to improve their business. Instagram benefits from its users creating their own user-generated content as it keeps them online longer; and the longer they stay on, the more money they continue to receive as profit for running the platform. It’s the same across TikTok, YouTube, Facebook, and all the platforms that exist across the internet.
Additionally, content creators also follow the “Golden Rule” of social media to help gain popularity. Proficient users of social media have claimed to crackdown the system of the algorithm and have created checklists for others to follow in order to efficiently produce content. Some of the major checkboxes follow those similar for businesses: posting with hashtags, following other creators/platforms who publish similar content, liking similar posts, sharing throughout various platforms, tagging other accounts, and the list goes on. Others may consider posting content that has the same appearance or aesthetics to take part in trends to reach more people within their targeted audience. Barnhart inputs that decoding, or outsmarting, the social media algorithm takes time to practice to understand even as a proficient creator and “the key is finding balance between what an algorithm wants and creating compelling content for your audience” (2021). One thing to note is that not everyone is the same and we all find interest in a variety of things. A variety of information is contained within the social media algorithm and it is up to the content creators to figure out what needs to be done to be efficient in their work online. In order for the system to work, the creator needs to make sure they determine the sole focus of their content and who it is for so that the algorithm can help aide where it can.
The social media algorithm is beneficial in many different ways despite what may still be unknown. Nevertheless, the main idea is that the system is entirely influenced by the users and stems from concept of choice and preference. Had the algorithm worked on a random generator of items, its most likely social media wouldn’t be as addicting and in high demand as it is now. It has developed and improve social communication, entertainment, and business.
BIBLIOGRAPHY
Agung, Nadia F. A. “Opportunities and Challenges of Instagram Algorithm in Improving Competitive Advantage.” International Journal of Innovative Science and Research Technology, vol.4, no. 1, 2019.
Barnhart, Brent. “Everything You Need to Know about Social Media Algorithms.” Sproutsocial, 2021.
Coolen, H., Boelhouwer, P., and Kees Van Driel. “Values and Goals as Determinants of Intended Tenure Choice.” Journal of Housing and the Built Environment, vol. 17, 2002, 215-236.
Dijck, Jose V. The Culture of Connectivity: A Critical History of Social Media. Oxford University Press, 2013.
Edosomwan, S., Prakasan, S. K., Kouame, D., Watson, J., and Tom Seymour. “The History of Social Media and its Impact on Business.” The Journal of Applied Management and Entrepreneurship, vol. 16, no. 3, 2011.
Figueiredo, C., and Cesar Bolano. “Social Media and Algorithms: Configurations of the Lifeworld Colonization by New Media.” The International Review of Information Ethics, vol. 26, 2017, 26-38. Irie, DOI: https://doi.org/10.29173/irie277.
Golino, Maria A. “Algorithms in Social Media Platforms.” Institute for Internet & the Just Society, https://www.internetjustsociety.org/algorithms-in-social-media-platforms.
Krumm, J., Davies, N., Chandra Narayanaswami. “User-Generated Content.” IEEE Pervasive Computing, vol. 7, no. 4, 2008, 10-11. IEEE, DOI: 10.1109/MPRV.2008.85
Towey, Monique. “The Secret Factors That Influence Your TikTok Algorithm and ‘For You’ Page Were Just Revealed. The App is Tracking How Long You Watch or Hover Over Videos.” Insider, 2013.
Zinas, Bako Z., and Mahmud Bin Mohd Jusan. “Housing Choice and Preference: Theory and Measurement.” Procedia – Social and Behavioral Sciences, vol. 48, 2012, 282-292. ScienceDirect, DOI: https://doi.org/10.1016/j.sbspro.2012.07.026.