Analyse everything facebook knows about you, through their own archive.
In light of the recent facebook's data breach, Mark Zuckerberg made all the data available for each user via Facebook. You're going to need to download it, we'll get to it shortly. There are some things that would take a lot of time (too costly API calls) online, but can be easily done on archived data.
Table of Contents
Getting the data
- Head on to Facebook > Settings > General Settings > Your facebook information.
- Select the JSON data format and click on download archive. It might take some time to prepare the archive, this might take upto 10-15 minutes. NOTE: The download might be in order of 100s MBs. Disable photo and video download options to save some bandwidth. (My archive was ~300MB).
- If possible, downlaod the same data in HTML format. It is much easier to browse through your archive and spot some interesting patterns in the HTML format, however this is not necessary. The JSON format will suffice for processing, refer #2.
Install requirements with
pip install -r requirements.txt
> python plot_friends.py Enter facebook archive extracted location: <location of extracted data folder, e.g.: "facebook-kaustubhhiware">
You can also run the script on sample data included in the examples folder:
> python plot_friends.py Enter facebook archive extracted location: ./examples
Will be updated soon
- Plot messages across all conversations.
> python plot_messages.py -a Enter facebook archive extracted location: "location of extracted, downloaded zip: like facebook-kaustubhhiware"
- Plot messages for a single conversation.
> python plot_messages.py Enter facebook archive extracted location: "location of extracted, downloaded zip: like facebook-kaustubhhiware" Enter id for friend: 511
What's this id?
- Open index.html in
- Click messages. Search for the person / conversation you want to analyse.
- Clicking on that chat should open a url like ; 'file:///home/kaustubh/GitHub/facebook-kaustubhhiware/messages/511.html'. For this particular chat, 511 is the id for this particular conversation. ↥ back to top
Your contributions are always welcome
Before working on an issue / feature, it is crucial that you're assigned the task on a GitHub issue.
- If a relevant issue already exists, discuss on the issue and get yourself assigned on GitHub.
- If no relevant issue exists, open a new issue and get it assigned to yourself on GitHub. Please proceed with a Pull Request only after you're assigned. It'd be a waste of your time as well as ours if you have not contacted us before hand when working on some feature / issue.
(Click to expand)
Plot the friends you make every day (blue), and the friends so far (orange).
The following is available for either a specific chat (person / group) or for all messages.
Plot all messages so far,
Plot the friends you make every day(Red) ,friend request send every day(green) and friend request received every day(blue)
Plot count of different reactions to posts
Your posts and comments
Wordcloud of common words in your posts and comments
There is a spike in friends made in March (Election season) and July (new juniors, much higher spike).
I tend to message less during exams (Feb, Apr, Sep, Nov).
Highest number of messages sent at 9 and 11 pm, confirming with calls from home come at 10pm. Almost no messages shared between 3am-7am.
I used to send more friend request as compared to friend request received.
I tend to receive more friend request in the month of july,august(new juniors)
I always wanted to know how many friends I make every month. It would have been infeasible to make a webapp out of this because so many API calls would be so slow, and whosoever wants to work with Facebook's Graph API?
Plus it was raining and I couldn't go to MS's Hall Day till after the rain stopped.
Have a feature request? See an interesting avenue not utilised yet with facebook's archive? Let me know by making a new issue.