https://github.com/avilum/facebook-archive-analyzer

This repository lets you explore, visualize and understand what data Facebook has about you.
https://github.com/avilum/facebook-archive-analyzer

data-visualization docker docker-compose elasticsearch facebook-archive kibana logstash

Last synced: 9 days ago
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This repository lets you explore, visualize and understand what data Facebook has about you.

• Host: GitHub
• URL: https://github.com/avilum/facebook-archive-analyzer
• Owner: avilum
• License: mit
• Created: 2021-02-01T22:11:10.000Z (almost 4 years ago)
• Default Branch: master
• Last Pushed: 2021-03-10T16:46:40.000Z (over 3 years ago)
• Last Synced: 2024-10-12T11:46:15.848Z (25 days ago)
• Topics: data-visualization, docker, docker-compose, elasticsearch, facebook-archive, kibana, logstash
• Language: Dockerfile
• Homepage:
• Size: 16.6 KB
• Stars: 21
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Facebook ZIP Analyzer - Explore Your Facebook Data Using ELK

This repository lets you explore, visualize and understand what data Facebook has about you.


All you need to do is go to the "Download Your Information" page, Download your private JSON archive at https://facebook.com/dyi/

## Setup

After you downloaded the archive, unzip it into the the folder "my_data", to the directory tree will look like this:

```code

mkdir my_data

# unzip your archive to my_data directory

# The repo tree should be:

..

docker-compose.yml

/my_data/facebook-/about_you

/my_data/facebook-/ads_and_businesses

...

```

Then, install docker-compose and docker locally.


Now, simply run the stack and see your data. 

The archive will be streamed to the stack from the files you just added to "my_data" directory using Logstash, indexed in ElasticSearch and visualized in Kibana.

```

# Optional - Install Docker:

#                            sudo snap install docker

#                            (https://docs.docker.com/get-docker/)

# Optional - Install Compose:

#                            https://docs.docker.com/compose/install/

# Run the stack:

docker-compose up

```

## Accessing The Dashboard

Now your data will be streamed, and within a minute you should see it on Kibana on http://localhost:5601/.

## See The Stack Logs

```code

docker-compose logs -f

```

## Add More Data To Logstash

You can add more files to the pipeline, by adding files to /logstash/pipeline/ and replacing the file path, and fields names to split.