Social Media Algorithm: How They Shape What We See
Have you ever wondered: how does social media and the internet seem to know your thoughts? Have you ever noticed how ads on your social media are uncannily aligned with your hobbies or interests? This personalised touch of the internet can be intriguing, yet it raises questions about privacy and how one can manage their online experience.
For some, the level of personalisation offered by social media is exciting, while for others, it can be quite scary. Social media platforms possess an astonishing ability to track our interests, and this capability is becoming increasingly sophisticated and less restricted.
The process began with search engines using algorithms to track general search histories, offering suggestions based on what other users searched for. This is the basis of Google’s auto suggest feature.
The internet has evolved to offer a highly personalised user experience, often reflecting our browsing habits and interests. For instance, if you start searching for guitars online, you might find your social media feeds filled with music shop ads or guitar videos the next day. This tailored content can be beneficial for some, making it easier to find relevant information. However, others might view it as an intrusive method to push advertisements and invade privacy.
Social media algorithms are designed to channel specific content to targeted audiences, increasing user engagement on the platforms. They determine what content users might discover outside their immediate circles.
Essentially, an algorithm is a set of instructions that processes data to solve a problem. In social media, the problem is connecting users with engaging and relevant content. Each platform employs its unique algorithms, which are continually refined to enhance user experience.
If you comment on, share, or like a piece of content, the algorithm registers this as positive feedback and will show you more similar content. Conversely, if you stop watching a video shortly after it starts, hide a post, or block content, these are negative signals, prompting the algorithm to show you less of that type of content.
Platforms like Instagram and Facebook provide transparency about why you’re seeing certain content. They might indicate that you’re seeing a post because you follow the poster, have liked similar posts before, or have interacted with related content.
Different platforms tailor their algorithms to match their specific focus, target audience, and the type of content they host. For example, YouTube, a leading platform for video content, provides recommendations based on popular live events, such as sports, which influence 70% of the content users watch.
LinkedIn, on the other hand, focuses on professional networking. Its algorithm aims to provide relevant content from colleagues, industry leaders, and brands, while filtering out spam. Engagement metrics like likes and comments play a significant role in its content recommendations.
Social media algorithms tailor content to its audience’s interests, while this customisation helps users find relevant information quickly, it can also feel intrusive. Understanding how these algorithms work can help us manage our online presence and set appropriate boundaries for our digital lives.
Kashish Kewalramani, the writer is a student of Economics at Manipal University, Jaipur and an intern at VeKommunicate