How Google's Patent Scores Authors and Posts on Messaging Systems

Google's 2013 patent describes a system for ranking authors and their posts on a messaging platform based on user interactions and subscriptions, influencing content visibility.

What it covers

This patent describes a way for a messaging system, like a social media feed, to figure out how important authors and their posts are. It calculates a 'score' for each author based on how much other authors interact with their posts (like commenting or liking them). Crucially, an author's score can also be influenced by the scores of authors who subscribe to their posts. When a new post is made, it gets a score based on the author's score. This post is then sent to authors who have subscribed to that author. The system can even decide to show the post to authors who *haven't* subscribed, if the post's score meets certain criteria, essentially promoting popular or influential content.

What it doesn't cover

• —Does not cover systems where author scores are determined solely by external factors, not by interactions within the messaging system.
• —Does not cover methods that don't consider authors subscribing to other authors' posts when calculating scores.
• —Does not cover systems that don't assign a score to individual posts.
• —Does not cover the transmission of posts only to authors who have explicitly subscribed to a specific author's stream.
• —Does not cover methods that don't evaluate if a post's score meets a criterion for wider distribution.

The clever bit

The innovation lies in creating a dynamic scoring system where an author's influence is not just based on their own content's reception, but also on the influence of those who choose to follow them, creating a layered measure of authority and reach.

Why it matters

This patent is foundational for understanding how online platforms, particularly social media and forums, manage content visibility and author influence. It provides a technical basis for algorithms that prioritize what users see, moving beyond simple chronological feeds to more dynamic, engagement-driven systems.

Real-world examples

• 1.Google+ (historical)
• 2.Modern social media feeds (e.g., Twitter, Facebook, Instagram)
• 3.Content ranking in online forums
• 4.Author reputation systems on collaborative platforms