You can use InfraNodus to visualize your WhatsApp chat or a group conversation in order to make sense of the main topics, find the gaps inside, and have bird eye's view on your interaction. You can then use the built-in AI to generate some interesting ideas on developing this conversation further or touching upon the topics that you haven't thought of before but that could develop your interaction in an interesting direction.
Importing Data from WhatsApp
WhatsApp provides API access to business accounts only, so it's quite hard to get the data from private conversations.
However, you can open a WhatsApp web browser and simply copy and paste the conversation into InfraNodus to visualize the main ideas and gaps within.
You can also format the data from WhatsApp in a special way so that you can filter the conversation by people to enable you to see who said what.
You will do that by running some operations on the text you copied to convert it into a CSV file (spreadsheet), where
• one column will contain the timecode,
• the second column will contain the name of the person who wrote a message,
• the third column will contain the message.
In order to do that,
1. Open a web browser on https://web.whatsapp.com and copy the conversation to a clipboard of your computer.
2. Open Visual Code text editor, create a new file, and paste the conversation into that file
3. Run Regex search and replace on the conversation to replace
3.a removing square brackets and putting the date inside parenthesis
Search for (set the regex on):
3.b remove the comma between the time and the date
where (1 is the first number of the date)
(repeat this for 0, 2, and 3 if those date numbers are present in your chat)
3.c put the name into parenthesis:
and then search for
3.c finish putting the statements into parenthesis:
3.d remove unnecessary paragraph breaks
3.e verify correctness
Your text should be of form:
5. Open InfraNodus and choose Import File > CSV Spreadsheet
6. Upload the file, then choose
• Statement column for analysis
• Name column for filtering / categorization
• Timestamp column for timestamping
7. Visualize the graph. You'll get something like this:
As you'll see, most of the conversations will tend to be quite technical, focusing on time-space arrangements. However, once you remove the most influential nodes, you may uncover some interesting topics underneath. You might also want to import the chats / group chats that are discussion groups about certain topics.
What to do with the Graph?
First of all, the graph shows you the main topics you covered and provides an interesting bird eye's view on your conversation.
You can use the How to Read and Interpret Text Network Graphs workflow to understand what the different parameters mean.
We encourage you to use the graph to ask yourself the following questions:
1. How do your expectations match reality?
Do you talk about things that you'd like to talk about?
2. Who says what?
Use the filters to see how the discourse differs for different participants
3. Find the main topics
What are the main topics you're talking about? Could this be different?
4. What are the gaps?
What's the parts of the discourse that could be better connected? Which two topics or clusters of ideas could be linked to produce some interesting results?