Influencer Detector is a system designed with the purpose of minning Facebook pages info and analyzing their relations in order to calculate influence levels within certain category over a predefined graph.
![alt text](https://github.com/dtoledo23/influencer-detector-front/blob/master/src/assets/img/Arquitectura.png?raw=true Influencer Detector Architecture)
- influencer-detector-front
- influencer-detector-back
- influencer-detector-crawler
- influencer-detector-analytics
We developed Influencer Detector as a school project in the Advanced Databases course. The team:
- Monserrat Genereux
- Victor Garcia
- Diego Toledo
Facebook Graph API mining. This module fetches data from the Graph API. It provides an API to enable requesting data over a POST request. It stores the results on Cassandra database. Go was chosen for this task to make the fetching process a lot faster by using goroutines and make concurrent calls to Facebook.
- Go 1.7
- Cassandra 3.0
- Run the cql scripts under
cassandra_init.cql
on your Cassandra instance
- Clone repo under
$GOPATH/src/github.com/dtoledo23
- You need a Facebook Page Access Token. Get one from https://developers.facebook.com/docs/pages/access-tokens
- Setup environment variables. Create a
.env
file based on the example under.env.example
go run server.go
- The app is already dockerized. Make sure you have
git
anddocker
installed on your host server. - Create
.env
file with the configuration needed. Take.env.example
format. - Build:
docker build -t influencer-detector-crawler .
- Run:
docker run -d -p 8000:8000 influencer-detector-crawler