Algorithms on social media platforms.

Algorithms on social media platforms: –


  • Algorithms on social media platforms can be defined as technical means of ranking posts based on relevance rather than post time, to prioritize what content a user sees first according to the likelihood that they actually interact with said content.
  • Coders using machine learning can write algorithms.
  • Machine learning means that algorithms learn to perform tasks under various levels of human supervision.
  • Algorithms handle various tasks that would be tedious for humans, such as managing content streams through active recommendations, as well as negative shadow bans, and mediating interaction with information through likes and comments to improve content visibility.
  • Algorithms classify and filter information in ways that create incentives and conditions for interaction for content creators that are similar to marketplaces.

Existence of algorithms:

  • The function of an algorithm is to deliver relevant content to users.
  • The reason social media platforms use algorithms is to filter more organically through the vast amount of content that is available on each platform.
  • Algorithms do the job of delivering content that is potentially more interesting to a user to the detriment of posts that are deemed irrelevant or low-quality, either in general or for a specific user.
  • Regarding criteria based on which algorithms deliver content, sometimes social media platforms explicitly specify what content they consider to be of high quality and therefore promote on their platform.
  • Also, it should be noted that social media platforms are real businesses, deriving part of their income from marketing.
  • This can include marketing a brand or content that public pages want to promote by paying a social media fee for algorithms to promote.

Algorithm work:

  • The algorithms are designed in a way that takes different aspects into account.
  • Some of these aspects are content-based, which means that this type of algorithmic design seeks to match a user’s taste, based on her profile, with specific posts that the system assumes the user will like.
  • Once users show interest in a specific tag or category, they are directed to other items in the same category.
  • Furthermore, the algorithms can operate collaboratively.
  • Collaborative filtering consists of matching users with other users who appear to share similar interests; in this way, a person is directed to posts or videos that they may want to see based on the fact that a user with a similar profile searched for that specific source.
  • Algorithms can be context-aware, in the sense that they can individualize personal data, such as the exact geographic location of a user, for inclusion in algorithmic calculations.
  • Finally, machine learning uses computers to simulate human learning, which allows them to identify and acquire knowledge from the real world, and improve the performance of some tasks, such as recommendations through algorithms, based on this new knowledge.

Algorithms influence the diffusion of culture in society:

  • These different approaches to algorithmic design have consequences when it comes to processing cultural content.
  • For example, when engineers configure computers through machine learning to create algorithms based on the geographic location of users, they limit, or at least direct, the spread of a particular art or information form to that specific area.
  • The effects of algorithmic design can be considered both positive and negative.
  • Oftentimes, algorithms can be created with the aim of increasing awareness or interest in the digital society on a specific topic, some users may suddenly see in their feed an increase of publications on nutrition and diet, foreign cinema or politics.
  • However, the negative implications that algorithmic design can have are often the subject of heated discussion in the controversies surrounding algorithms.
  • These controversies often concern privacy issues:
  • Algorithms work with the personal data of the social media user to know how to display content on the social media platform (for example, algorithms use sensitive data such as the geographical location of the user, the friends and acquaintances with whom they interact the most, the pages and hashtags they usually search for, etc.).
  • Similarly, there are also considerations about how algorithms influence the opinion and interests of users of social networks and, consequently, of the digital society.
  • By using shady bans, algorithms can lead to information gaps by hiding or neglecting certain posts while prioritizing revenue-generating content.
  • This aspect of algorithmic design is controversial because it is intended to determine what content users should consider important or worthy of appreciation.
  • This can lead to a polarized and non-objective decision of who and what is put in the limelight.
  • As a result, algorithmic design inevitably influences the diffusion of culture and shapes the digital society in a certain way:
  • It decides what kind of content or topic should take priority in each individual feed, and which artists, content creators or brands deserve. to win. more visibility than others.


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