The Rise of the Algorithm

As I was just placing my phone down to start working on this post, I scrolled through one last Instagram story. In this story, a local account detailed their experience making homemade pumpkin pie today. In this multi-story post, they broke down each step while writing small sections of text that one would need to know in order to follow the recipe. As casual as this may seem, Christine Wolf’s piece touched on this scenario directly. Wolf states that Web 2.0 now “[allow s] users to generate and distribute their own content can support informal and self-directed learning” (Wolf, 2016.) After reading this statement from “DIY Videos on Youtube” by Christine Wolf, I immediately connected to what I just engaged with moments before. Personally, I never have baked a homemade pumpkin pie from scratch, but the organic content generated from the Web 2.0 structure allowed me to self-learn a new skill. 

Now, I only was able to see this story pop up first on my feed since the Instagram algorithm tracked that I watch this specific account’s stories routinely. Thus, this leads the story to be seen first on my homepage when I log into the application. I was not presented with that DIY baking video by accident, rather, the algorithm is in control.

As a person who has dabbled in creating their own creative content, I struggle to appease the social media algorithm. It seems as though it maintains a mind of its own, placing content and audiences into invisible groups. Algorithms can guide us to engage in our passions and niches on internet platforms. At times, algorithms can even present us with new content that we end up admiring. However, algorithms also box-in and categorize users into certain groups. On one end, this seems like a helpful tool to present users with content they enjoy while keeping them logged into the platform.

Subsequently, algorithms also stop the transfer of new knowledge into the user’s algorithm created bubble. For example, if I only watch YouTube videos on how to garden, there is a large chance I will never be presented with exercise content. Maybe the user would not want to see different content, but maybe they would want to be brought outside their echo chamber as well. This situation that Wolf mentions reminds me of another Web 2.0 experience I had just a few days ago. It is true that “algorithms also shape individuals’ experiences with Web 2.0 platforms in many ways” (Wolf, 2016). I recently downloaded Tik Tok, mostly to understand why the application serged into popularity this year. Before downloading it, my only concept of it was a platform where people choreographically danced to music in small sixty-second videos. That type of niche did not interest me at all, but when I created my Tik Tok account, totally different content filled the screen. I was surprised to notice that the same niches I followed on other platforms appeared in my Tik Tok feed as well. It was almost like the overarching Web 2.0 algorithm already knew what I would like. Instead of watching dances, I interacted with the application in a totally different way than what I thought I would. My experience and concept of the application changed due to the algorithms prior notions about me.

As interesting as I find this, I feel like it also has negative consequences as well. Gone are the days where content is completely and freely flowing into your space if there was ever such a day!

Posted on September 27, 2020, in Social Media. Bookmark the permalink. 4 Comments.

  1. Hi Baily,

    I can connect to your story, I too like cooking but have never had any official culinary teaching and am definitely more of a “Google chef.” I like you present the double-edged sword aspect of internet algorithms. While on one hand, they expose a user to very niche and specific content, it also confines them to a smaller bubble in terms of the type of content they see. I just started watching The Social Dilemma on Netflix and am partway through, it seems like this documentary sheds a lot of light on the elusive algorithm. It is strange to consider that a person’s experience and concept of an application, like YouTube or Tik Tok in your example, can be completely different from another person’s based on their algorithm. I’m not sure if you’ve ever experienced this before, but sometimes going into an app through a new account or someone else’s can be very surreal with how different everything looks.

    Great post!

  2. rebeccaanderson8641

    Hi Bailey,
    Very interesting work! I have fallen victim to the YouTube algorithm as of late as my daughter immensely enjoys Baby Shark videos. I have an odd mixture of Baby Shark, political podcasts, and lectures in my recommendeds.
    I wanted to ask your opinion on the polarization of the internet. A commonly recognized phenomenon is online echo chambers in which people find a group of common thinkers and aren’t exposed to much content outside of that thought stream. Originally, I assumed the main cause of this was just the sheer numbers of internet users. People even with fringe view points on certain subjects can find camaraderie. However, do you believe that algorithms contribute to this phenomenon? Bringing you more and more content that aligns with your interests and perspectives does have the potential to cut you off from oppositional viewpoints.
    Great work!

  3. Hi Bailey,

    I found this post extremely interesting! I have been noticing a spike of comments like, “See you all in five years when this video gets recommended to you”, or, “We both know that you didn’t search for this video”, recently and it has really made me think about how the YouTube algorithm actually works. I have never really understood it but it has fascinated me in how YouTube chooses what videos you get to see and what videos you don’t get to see. I found it exciting when YouTube just seems to know what I am looking for. For example, I would listen to music on YouTube when I am doing homework. As YouTube cycles through music, it always seems to know exactly what I am looking for. I can click on a video of “Crawling” by Linkin Park and the algorithm would not only just cycle through songs that sound similar, or songs specifically by Linkin Park, but would cycle through different rock songs of the 2000s era specifically ranging from metal to pop-punk. This surprised me when it happened the first time as I was not expecting the algorithm to know exactly what I was looking for. This was also how I rediscovered old songs from the era that I loved but had completely forgotten about such as “Dear Maria, Count Me In” by All Time Low.

  4. Hi Bailey!

    Great post! As of late, I’ve been feeling overwhelmed by the algorithm. I even went as far as to “hide” all the content on Instagram that the platform knows I’m interested in and “liked” content that went outside my bubble – a social media refresh. While I enjoy the recommendations to some degree, I find it to be overpowering, limiting my ability to learn new topics. I always find it interesting to look at another person’s feed compared to mine. It’s like entering a whole new world!
    I still hold onto a few accounts that I follow regularly. Like the post you shared, I follow several cooking accounts that support “self-directed learning.” DIY culture boosts users’ confidence and reduces the fear of attempting something new or taking up a new hobby. I find it helpful when videos are attached to the content, especially with recipes.

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