Research any topic before you write.

Find related topics. | Discover entities. | See connections. | Build a topical map.

EdgeRank: Art, Impact & Overview

EdgeRank is the name commonly given to the algorithm that Facebook uses to determine what articles should be displayed in a user's News Feed. As of 2011, Facebook has stopped using the EdgeRank system and uses a machine learning algorithm that, as of 2013, takes more than 100,000 factors into account.

Language: English [EN]
Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.
100%
More settings
100% 100% 100% 100% 100%

EdgeRank topic overview

The analysis highlights Art, Impact and Overview as prominent areas in the source structure around EdgeRank.

Related topics
8
Source areas
2
Connected nodes
10
Extracted relationships
5
Concept neighborhoods
8
Bridge connections
10

What this topic covers Research coverage

Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.

Overview · 5 topics
Impact · 3 topics

Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.

Explore all related topics Closing gaps

Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.

Overview

Impact

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

How EdgeRank connects Entity context

The extracted context around EdgeRank shows recurring relationship patterns in the source. For example, EdgeRank → As, Facebook Another extracted example is EdgeRank → name commonly given to the algorithm that Facebook uses to determine what articles should be displayed in a user's News Feed. Use these groups to spot repeated connection types before inspecting the individual relationships.

EdgeRank

Top relations

has impact · 2
EdgeRank → As, Facebook
is a · 1
EdgeRank → name commonly given to the algorithm that Facebook uses to determine what articles should be displayed in a user's News Feed
related to External links · 1
EdgeRank → How News Feed Works
related to Formula and factors · 1
EdgeRank → In

Important terminology

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

facebook algorithm uses content reach factors organic news feed impact see user shown like reaction haha comments ranking pages name

EdgeRank relationships Subject–Predicate–Object triples

TTTA extracted 5 structured relationships around EdgeRank. Examples in this analysis include EdgeRank → is a → name commonly given to the algorithm that Facebook uses to determine what articles should be displayed in a user's News Feed and EdgeRank → has impact → As. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
EdgeRankis aname commonly given to the algorithm that Facebook uses to determine what articles should be displayed in a user's News Feed0.90text
EdgeRankhas impactAs0.60section
EdgeRankhas impactFacebook0.60section
EdgeRankrelated to External linksHow News Feed Works0.60section
EdgeRankrelated to Formula and factorsIn0.60section

Related concept clusters Concept neighborhoods

The concept neighborhoods around EdgeRank bring nearby vocabulary together. In this analysis, examples include Algorithm, Facebook and Factors. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

  • EdgeRank
    • Algorithm
    • Facebook
    • Factors
    • Feed
    • Impact
    • News
    • See
    • Uses
    • Account
    • Articles
    • Commonly
    • Determine
  • edgerank
    • Algorithm
    • Facebook
    • Factors
    • Feed
    • Impact
    • News
    • See
    • Uses
    • Account
    • Articles
    • Commonly
    • Determine
  • algorithm
    • Edgerank
    • Factors
    • Feed
    • News
    • Facebook
    • Uses
    • Account
    • Articles
    • Commonly
    • Determine
    • Displayed
    • Given
  • facebook
    • Uses
    • Feed
    • News
    • Ranking
    • Account
    • Given
    • Learning
    • Machine
    • Name
    • Stopped
    • System
    • Takes
  • machine learning
    • Learning
    • Machine
    • Stopped
    • System
    • Takes
    • Using
    • Factors
    • Uses
  • news feed
    • News
    • Given
    • Name
    • User's
    • Ranking
    • Uses
  • organic reach
    • Reach
    • Pages
    • Reaction
  • impact
    • See
    • Shown
    • User

Connections between topic areas Semantic bridges

For EdgeRank, one of the stronger structural bridges in this analysis connects EdgeRank with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.

Min side: 3
EdgeRank — Overview · splits 5 ⟂ 6
EdgeRank — Impact · splits 7 ⟂ 4

Map overview Semantic statistics

EdgeRank

Nodes11
Edges10
Triples5
Avg. degree1.82
Density0.181818
Components1

Source & methodology

TTTA analyzes the structure around EdgeRank to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Art, Impact & Overview, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — EdgeRank · EN edition · Analysis: TopicsToTalkAbout

For writers, content strategists, SEOs, marketers and creators — from quick topic research to advanced semantic analysis.