Facebook news feed algorithm 2018 youtube

The Facebook News Feed algorithm is a complex system that determines what content to show to each user, and how to rank that content in their News Feed. Here's an overview of the Facebook News Feed algorithm in 2018, as explained by Facebook's engineers and researchers:

Ranking Factors:

  1. User Engagement: How much time users spend engaging with a post, such as liking, commenting, or sharing.
  2. Post Relevance: How relevant the post is to the user, based on their interests, preferences, and previous interactions.
  3. Post Quality: The quality of the post, including factors such as the credibility of the source, the accuracy of the information, and the overall quality of the content.
  4. User Behavior: How users interact with the post, such as whether they hide or report it.
  5. Post Timing: When the post was published, and how recently it was published.
  6. User Relationships: The relationship between the user and the person or page that posted the content.
  7. Post Type: The type of post, such as a photo, video, or link.

How the Algorithm Works:

  1. Crawling: Facebook's algorithm crawls the web to gather information about each post, including the content, metadata, and user engagement.
  2. Indexing: The algorithm indexes the gathered information, creating a database of posts and their corresponding ranking factors.
  3. Ranking: The algorithm uses the ranking factors to rank each post in the user's News Feed, with the highest-ranked posts appearing at the top.
  4. Filtering: The algorithm filters out posts that are likely to be irrelevant or low-quality, such as spam or duplicate content.
  5. Personalization: The algorithm personalizes the News Feed for each user, based on their individual preferences and behaviors.

Changes to the Algorithm in 2018:

  1. Increased Focus on Meaningful Interactions: Facebook emphasized the importance of meaningful interactions, such as comments and shares, over likes and other superficial engagement metrics.
  2. Reduced Prominence of Clickbait and Spam: Facebook's algorithm became more effective at detecting and demoting clickbait and spammy content.
  3. Improved Video Ranking: Facebook's algorithm became more effective at ranking high-quality video content, including live videos and videos with high engagement.
  4. Enhanced User Feedback: Facebook introduced new ways for users to provide feedback on the algorithm, such as the ability to hide or report posts that are not relevant or high-quality.

YouTube Algorithm:

The YouTube algorithm is a separate system that determines what videos to show to each user, and how to rank those videos in their search results and recommendations. Here are some key factors that influence the YouTube algorithm:

  1. Watch Time: How long users watch a video.
  2. Engagement: How users interact with a video, such as liking, commenting, or sharing.
  3. Relevance: How relevant the video is to the user's search query or interests.
  4. View Count: The number of views a video receives.
  5. Likes and Dislikes: The number of likes and dislikes a video receives.
  6. Comments: The number and quality of comments on a video.
  7. Shares: The number of times a video is shared.
  8. Watch History: A user's watch history, including the videos they've watched and how long they watched them.
  9. Search History: A user's search history, including the keywords they've searched for and the videos they've watched as a result.
  10. Device and Location: The device and location from which a user is accessing YouTube.

How the YouTube Algorithm Works:

  1. Crawling: YouTube's algorithm crawls the web to gather information about each video, including the content, metadata, and user engagement.
  2. Indexing: The algorithm indexes the gathered information, creating a database of videos and their corresponding ranking factors.
  3. Ranking: The algorithm uses the ranking factors to rank each video in the user's search results and recommendations, with the highest-ranked videos appearing at the top.
  4. Filtering: The algorithm filters out videos that are likely to be irrelevant or low-quality, such as spam or duplicate content.
  5. Personalization: The algorithm personalizes the video recommendations for each user, based on their individual preferences and behaviors.