Thread by @GiordMarco96

Continuing in the wake of Semantic #SEO, today we talk about Knowledge Graphs, a very interesting topic that represents the intersection between graphs and SEO.

This is a Semantic SEO thread 🧵

#NLP #DataScience

A Knowledge Graph is a set of entities and relationships, that is all you need to know as an SEO Specialist to begin with.

Each entity can have attributes, namely characteristics/details.

Let's take a step back, what is a graph?

You can think of it as "a set of nodes/vertices and edges/links". Graphs are referred to "networks" as well.

The picture below displays an example of what is a graph.

Source: geeksforgeeks.org/graph-data-str…

Google and LinkedIn make use of such data structures, for instance.

In other words, they are very useful to improve information retrieval, information from graphs is way better than just counting keywords on a page.

The main idea here is to create topical maps that are actually knowledge graphs, thinking of your website as a big network of entities rather than a set of pages.

Therefore, you can treat topics extensively and leverage connections between pages via effective internal linking.

This means you will link pages among each other with the most reasonable anchor text and considering their hypothetical relationship in your topical map.

Google has its own Knowledge Graph and you can actually query it!

If you have expertise about something (i.e. your Knowledge Graph makes sense) Google may consider you as someone proficient, an authority in your field and that is where topical authority comes into play.

Some more resources about Knowledge Graphs for SEO:

Overview in Python:
holisticseo.digital/python-seo/kno…

The most technical material ever, ideal for advanced users:
seobythesea.com/category/fact-…

An awesome introduction:
wordlift.io/blog/en/entity…

A reminder about Semantic SEO as a whole and about entities and Named-Entity Recognition:

https://twitter.com/GiordMarco96/status/1483581803701100546