BERT Explained: Bidirectional Encoder Representations from Transformers

What is BERT?

BERT (Bidirectional Encoder Representations from Transformers) is Google’s primary ranking factor/signal. It is an NLP (natural language processing) model created by Google’s AI team.

In 2018, Google converted BERT to open-source so that anyone can take benefit of this NLP model. BERT can handle many NLP-related complex tasks.

Tasks BERT can perform

A few of the complex tasks performed by BERT are:

1- Text Sentiment Analysis:

BERT can analyze and understand whether the review of a product/service/movie is positive or negative. And can also check if the sentence/paragraph expresses anger, happiness, joy, etc.

2- Chatbots:

Chatbots are used to answer questions naturally.

3- Summarizing a long article:

BERT can read a long-form article and then quickly summarize it.

4- Text Prediction:

If you are typing something, the keyboard can automatically sense what next word you want to type. (Typing inside Gmail email is an example of a BERT/NLP feature.)

5- Article Writing:

BERT/NLP can write an article on any topic using their Artificial Intelligence.

6- Comments Detection:

It can detect good or bad comments. It can understand the comment’s text and decide which comments are harassing, bullying, or bad.

7- Speech to Text:

It can transcribe audio to text. With the help of the NLP model, it can perfectly transcribe speech to text.
Even before BERT, Google was performing the tasks mentioned above. But BERT has improved the accuracy and the quality of the results of these tasks.

Importance of BERT

‘B’ means Bi-directional, as the name indicates.

Before BERT, all the language models were processing the text either left to right or right to left direction, but BERT can process/analyze the content in both directions.

Then comes ‘E’ means Encoder.

To understand the Encoder, first, we must understand what is ‘T’ in the Transformers.

What is Transformers in BERT?

In AI, the Transformer is a mechanism that can analyze the relationship between two words.
The example can be, if you type “Apple,” it can be interpreted as a fruit as well as the Apple company. But based on the ability of Transformers to understand the relationship between two words (in both directions), Transformers can understand which Apple is being discussed in the text.

Google’s Transformers consists of two parts:

1- Encoder

Encoder means input text. The Encoder analyzes the given text to understand its meaning.

2- Decoder

Decoder means output text. The Decoder gives the results based on the Encoders analysis report.

In BERT, Google uses just the Encoder and not the Decoder because the primary job of BERT is to understand the relation between the text and sub-text. But not to output/decode the relationship results to the public.

How BERT affects SEO?

Google utilizes BERT for SEO in four different ways.

1- Understanding Query:

When people type their Query in Google’s search box, BERT can understand those queries better than the predecessor updates. And based on this new understanding system, it can show users much better relevant search results.

2- Understanding Emotions:

BERT can analyze and understand the mood/sentiments of your page content. Like, if your page content is positive or negative, you are targeting any specific type of community by harassing them and likewise. BERT can efficiently perform such complex tasks and understand your article’s emotions.

3- Understanding Quality:

BERT can perfectly understand the questions and answers. Therefore, if you are trying to rank your page for any specific question, ensure that you give the right and to-the-point answer because Google knows everything now!

4- Understanding Entity:

If your post/page/article is about any entity, e.g., person, place, monument, country, brand, date, company, etc., then BERT can easily understand that Entity.

What to change in the website to achieve BERT?

How can SEO and content writers optimize their pages and content? Or how can BERT rank your website in a better way?
Here is the answer:

1- Stop words:

In the past, stop words (e.g., to, the, from, a, for, etc.) were ignored by Google; therefore, people thought that these stop words had no meaning. But now Google can understand the stop words and their relation with the next/previous word.
Therefore, now the stop words are the “Go Words.”
Because these “Go words” tell BERT about the sentence’s meaning.
Therefore, for the Title, Description, or content, watch your grammatical errors and naturally write perfect sentences.

2- Keyword Density:

Do not use your target keywords unintentionally, unnaturally, or forcefully. Because BERT can now easily read and understand the mood/emotion of your content. BERT will catch you in a gist if you use your keyboards unnaturally. And that will help drop your page rank. (No one wants that, right?) Keep your content natural looking. Use keywords but in a natural way.

For reference: Here is the list of → All 19 Most Important Google Ranking Signals for 2023.

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