Show HN: Visualizing 9 years of relationships with instant message frequency(hipsterdatascience.com) |
Show HN: Visualizing 9 years of relationships with instant message frequency(hipsterdatascience.com) |
The hardest part was matching hundreds of friend's various usernames across different services to the same person. It's a process that's difficult to automate, even with some helper scripts it took a couple days to manually curate the mapping.
The svgs for the grid are in pre-rendered static files made with node/jsdom, which was pretty fun to write.
Data sources:
Skype history file
Facebook data download
Google Voice and Google Hangouts data download
Email (for oldschool gchats)
iPhone backups, for SMS/iMessage
Slack API
Symbian and Android had options to extract to xml/txt. But after I got Windows Phone and iPhone, it is harder for me to extract all texts but they are there in the cloud. I will have to extract and normalize them somehow.