A Mirror of Thoughts: Personalized Social Media Algorithm

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COMPFEST

5 min readJul 16, 2024

Have you ever found yourself scrolling through social media and think, “This is so me”? It’s that moment when you come across content that perfectly matches what you’re thinking about lately — things you’re interested in or ideas you seem to agree with. This phenomenon is part of the advancements in social media algorithms, but how does it actually work?

Evolution of Social Media Algorithms

Social media algorithms were initially designed for chronological display. Feeds were structured based on the order in which content was posted. Upon opening the app, the earliest content to appear would typically be the most recent. Initially, these algorithms relied heavily on the pages a user followed, presenting a straightforward feed of updates. However, as the volume of content grew exponentially, social media platforms also shifted towards personalized algorithms. This approach tends to increase user engagement by aligning closely with their preferences and interests.

How Does It Actually Work?

It revolves around data analysis based on user engagement data. Basically, this includes tracking our clicks, likes, and shares on different types of content. These interactions are then analyzed to understand the kind of content we prefer, the topics we are interested in, and the people we interact with the most. For example, if we often like posts about cooking, the algorithm then analyzes two perspectives:

Towards other cooking-related posts: Would we enjoy those based on our past interactions?
Towards us: Are there more similar types of content that we might be interested in based on our previous engagements?

Impact on User Experience

The way social media algorithms personalize content significantly affects how users experience the platform. By showing content that matches a user’s interests and actions, users tend to be more satisfied. This is because they see fewer things they don’t care about and more of what they like. As a result, users also spend more time on that platform.

Filter Bubbles

Filter bubble is a term popularized by Internet activist Eli Pariser. Being in a filter bubble means outside information is blocked from reaching a user. This “outside information” includes perspectives that differ from what the user typically engages with or believes in. Users may not even realize they are in a filter bubble, becoming isolated without awareness. When many people are stuck in their own bubbles, misunderstandings can arise because they only encounter information that aligns with their existing beliefs. In essence, they believe what they want to believe.

Algorithmic Bias

Long ago, humans tended to learn from members of their own group or from prestigious individuals, as their information was considered more reliable. This “bias” is connected to the source of the information itself. Now, with social media algorithms in place, the focus has shifted subtly to our existing prejudices. Popular ideas spread quickly, and users are more likely to interact with posts that have many likes. Subsequently, the algorithm promotes similar content, leading to a cycle where only popular or mainstream ideas are highlighted, while other important perspectives are overlooked.

Manipulation and Addiction

Social media algorithms are designed to keep users engaged, but this can sometimes lead to manipulation and addiction. A user’s psychological vulnerability is exploited through addictive content. Once the user is addicted, it’s hard to stop using the platform, even for a short while. Additionally, algorithms can manipulate user behavior by repeatedly promoting certain ideas or products, subtly influencing decisions and opinions.

User Privacy

Personalized social media algorithms raise concerns about how deeply user data is used. To suggest content, algorithms analyze data such as age information, browsing history, and even location. While this enhances user experience, it sparks debates over data protection and ethics regarding user privacy. There are laws and regulations addressing these issues, emphasizing the need for consent from platform users.

Personalized Ads

Have you ever searched for something online, only to see an advertisement for it when you open social media? That’s direct personalization. Another example is indirect personalization: if you like posts about journaling, you might start seeing ads for journals and other related products. This happens because the algorithm connects everything on your phone to tailor ads to your interests. This kind of personalization makes people more likely to buy things when they’re inspired or interested in a topic, leading to successful marketing strategies.

Role of AI

The role of Artificial Intelligence (AI) is absolutely essential. AI acts as a smart assistant that personalizes content and connects different pieces of information. It analyzes data tracked from user engagements. These AI-powered algorithms continually learn by consuming new data, improving their ability to predict personalized content. That’s why the longer we use a platform, the more it feels like “us”. It’s just the AI working nonstop.

The Future of Social Media Algorithm

Looking ahead, the future of social media algorithms will be shaped by continuous advancements in AI and machine learning. Technologies will become more accurate and precise in predicting and understanding user preferences. A potential advancement may focus on ethical considerations, aiming to reduce biases and ensure more diverse content. Additionally, there will likely be stronger efforts to protect user privacy and data security.

Conclusion

Social media algorithms act as a mirror of our thoughts, reflecting our interests, behaviors, and preferences. They have revolutionized the way we interact online by offering super-personalized content that aligns closely with us as individuals. However, this close reflection may create phenomena such as filter bubbles, raising ethical questions about the aftermath. Ethical concerns are particularly raised regarding privacy, bias, and the potential for manipulation. Understanding the impact of these algorithms is essential for us to navigate the internet and social media responsibly.

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