Unlike Amazon or Yelp, Social Media Algorithm Rankings Are Not Based On Reliability or Quality
People often check out reviews of products they buy on Amazon to not only check whether the product has good reviews, but to see if it has a lot of reviews, particularly if the reviews are made by someone who has been verified to have purchase the product. Likewise, people will often check out Yelp reviews of restaurants in a similar manner and a restaurant that does not live up to the hype is often stricken with negative reviews by disappointed diners, which often negates efforts to create fluff reviews.
So, wouldn't it be natural to look at social media rankings and recommendations in the same way? After all, shouldn't we assume that a story that is trending and "going viral" is doing so because it is true? I think many people would be surprised that the reason why a story might be going viral is because it is sensationalistic and false, thus people will not only watch it, but might even forward the story to others. Yet, there is no warning or disclosure that social media stories are not being ranked or recommended based on accuracy or reliability like an Amazon or Yelp review. Instead, the story could be ranked high because it is outrageous and generates an emotive responsive that causes people to react to it both positively and negatively.
Moreover, social media algorithms help create self-made echo chambers that serve to reinforce views' opinions, because as they watch content with a certain bias, they get more content that reflects that bias, which they watch, which reinforces the bias, as well as the algorithms tendency to show similar content. Thus, an anti-vaxxer will naturally get content that tends to show that vaccines are ineffective, without any disclosure that the rankings are not based on accuracy, reliability or any type of journalistic standards.
https://dhananjaymittal.medium.com/algorithmic-bias-reinforcing-prejudice-on-social-media-46de22eef5dc
Social media platforms have become a ubiquitous part of our lives, offering personalized content that caters to our interests and preferences. Behind this personalization are complex AI algorithms that aim to enhance user experience. However, there’s a concerning downside to this technology — algorithmic bias. In this extensive blog, we will delve into the world of algorithmic bias on social media, exploring how these algorithms may unintentionally favor certain groups and viewpoints, ultimately contributing to discrimination and inequality.
Social media platforms like Facebook, Twitter, and Instagram have revolutionized the way we consume content. They employ sophisticated algorithms that take into account your past interactions, likes, shares, and comments to curate a feed that aligns with your interests. This personalization is designed to keep users engaged and active on the platform.
While personalization enhances the user experience, it brings forth a concerning phenomenon known as the “echo chamber effect.” This term refers to the way algorithms often feed users content that aligns with their existing beliefs and preferences. In other words, if you tend to engage with a particular political view or set of interests, the algorithm will continue to serve you content from that perspective.