Step 2 Keyword Research: Free Script Clustering Keyword
Let's discuss more seriously how to run the keyword clustering script. To fully focus, prepare your favorite drink and snacks first.
Main Requirements for Performing Keyword Clustering
Before delving into a more in-depth discussion, there are several prerequisites that you must fulfill first. This is crucial! If you want the best results, ensure that you have completed the script checking and remove process similarity keyword for free and copied the Script. Once you have finished, you can proceed to the next step. Let's continue reading, friends!
Step-by-Step Guide to Running the Keyword Clustering Script
Now, let's discuss more seriously how to run the keyword clustering script. To fully focus, prepare your favorite drink and snacks first. Let's begin, friends!
Step 1: Prepare Unique Keywords
This is very important! This is why I suggest completing the similarity checking process for free. Why? So that you can obtain unique keywords. So, for those who already have unique keywords, proceed to the next step. For those who haven't, don't be lazy, finish it first! It's an obligation!
Note: If you notice, when you perform a similarity check, the downloaded keyword results are named "unique_keywords.csv." You just need to change it to "keywords." Easy, isn't it? Okay, let's move on to the second keyword clustering step.
Step 2: Upload Unique Keywords
To upload unique keywords, you need the help of Google Colab. Now, open Google Colab.
Step 3: Create Configuration File
The keyword clustering script you will input this time will import all the modules needed by the system to run smoothly. In this step, you also need to change some parameters, namely "language."
Note: I am targeting keywords in Indonesian, so I change "language" to "indonesian." If you are targeting French, for example, you can change it to "french." If confused, check in the metatext, it's explained completely. So as not to be confused, here's how to change it.
ctrl + f -> type "language": "indonesian" -> Change the language
Step 4: Install Python Libraries
This keyword clustering script runs using the Python programming language, so the system needs to install its libraries.
Step 5: Import and Detect Each Word in Keywords
In this keyword clustering step, you will import all the necessary Python libraries and then proceed with the process of detecting each word in the uploaded keywords. Let's input the script.
Step 6: BERTopic Modeling
Since this script uses the BERTopic modeling technique, you will directly run the script based on each word in the detected keywords, then group them automatically according to the BERT algorithm.
Note: At this stage, you also need to change the target language as needed. Here's how:
ctrl + f -> type "language=config.get('language', 'indonesian')" -> Change the language
Step 7: Save the Clustered Keyword Result Files
After the BERTopic modeling process is complete, the last step you need to do is input the script to save the generated files. Thus, you will get two files, "clustered_keywords.xlsx" and "outliers.xlsx."