Personalized Algorithms

Benefits of Personalized Algorithms

Personalized algorithms can deliver a more engaging experience when scrolling through social media. Posts that receive more likes and comments are more likely to appear in your feed, filtering out content that may uninterest the user. The algorithm helps curate content that matches the user’s interests and reduces potential clutter. When a user chooses to interact with a post, the algorithm learns their interests to best fit their preferences.

Businesses see significant benefits to personalized algorithms when properly investing and understanding their roles in social media feeds. When businesses have a pulse on current trends and interests, they can create content that fits with those ideas and engage more users. Younas (2025) states that “the social media algorithm promotes your content to a broader audience when it is highly engaged. This helps creators and brands grow their online presence by reaching more people on the platform”.

The way that information is delivered on social media has empowered advocates of free speech. Anyone has the ability to share information widely, and the algorithm can help deliver those messages should they resonate with others. While restrictions are certainly in place, information is more widely distributed and instantly shared than ever before. An algorithm can help promote posts related to safety as well, an example being a forest fire nearby where people in the area need to be notified for an evacuation. 

Ethical Aspects of Personalized Algorithms

In theory, the idea behind personalizing the content of someone’s algorithm may appear harmless. Companies anticipate what their customers may want and content that the user may want to see can be prioritized. Content then becomes more relevant when tailored to a user’s interests. When content that a user will likely not engage with disappears, it makes their social media feeds more relevant and interesting. 

Is it harmful for Spotify to suggest a song you may enjoy based on previous listening habits? Perhaps not, but the concern surrounds how Spotify is predicting what content you may enjoy. “As personalization becomes more pervasive, ethical dilemmas arise, especially when it comes to how user data is collected, used, and shared. Personalization often requires extensive data gathering, and users may not always be aware of or comfortable with how much of their personal information is being used to create these tailored experiences” (Zaytseva, 2024).

The way data is collected is often not very transparent and can be perceived as manipulative of someone’s privacy. While I may get a chuckle out of seeing an advertisement based on something I said in a conversation with someone else, the more I reflect on that method of collecting data, the more disturbed I feel. This collection method is a serious invasion of privacy where the risk may outweigh the benefits. Social media apps generally have a method for turning this feature off, though many users may not realize this or care to figure out how to do so. Rather than data collection being the default setting, users should be able to opt-in to this feature. These personalized presentations may appear to be to the user’s benefit, but really it is large corporations who are profiting from consumers being manipulated by these personalized algorithms.

Personalization of algorithm content can also lead to echo chambers where personal views are not challenged. As political tensions throughout the world grow, users become stuck with unwavering views brought on by the frequent confirmation bias occurring from their social media apps. The constant exposure to their own opinions creates viewpoints that are limited and uninterested in diverse perspectives. Social media’s personalized algorithms potentially make the world appear more polarizing than it really is.

Social Media Feeds

Facebook

Facebook’s algorithm uses AI to curate a feed based on these conditions:

• The poster of the content

• The chance that a user might engage

• The media type

• Interaction frequency

Instagram

Instagram’s algorithm prioritizes the following factors:

• Higher engagement posts (likes, comments, shares)

• Recent posts

• Users who frequently post

• Interactions with other users

Twitter (X)

Twitter’s algorithm differs slightly from others:

• Favours content that is currently trending

• Real-time conversations prioritized 

• Posts shown from outside of who you are following

• Text-first rather than media-first

• Less personalization than Facebook/Instagram

TikTok

Here is how TikTok uses their algorithm to generate their “For You” page:

• Analyzes media you watch to suggest new but similar content

• Checks for how long a video was viewed for

• Considers whether a video was replayed

• Videos with high engagement outside of a user’s typical interests may be displayed

• A user’s region is considered and what is currently popular in the area

Personalized Advertisements

Personalized advertisements generated by collecting a user’s data is certainly a great marketing strategy for corporations to make a profit in today’s competitive markets. The main concern around this advertising method surround the actual user and their right to privacy. The method in which this data is collected may be problematic to some users, specifically the use of microphones picking up private conversations or search history data. For other users, this method of advertising may be seen as convenient or user-friendly.

In the age of information, companies may notice more competition due to the vast amount of choices consumers have with online shopping. According to Lina & Setiyanto (2021), “Consumers are always looking for information through various media before buying a product, from reviews in e-commerce, reading content and blogs or from influencers” (p. 149). Consumers have an overwhelming amount of products and information at their disposal, targeted advertising through acquired personal information may feel helpful for the overwhelmed shopper. Perhaps companies should prioritize transparency, ensuring consumers can tell what data is being collected and how. Giving consumers the option to opt-in to data collection rather than opt-out should be user-friendly for all mobile users.