Scaner, Social Context Analysis aNd Emotion Recognition is a platform to collect and analyse social context, i.e context of users and content in social media. In particular, Scaner detects possible influencers and assess their relevance and impact capabilities in a given topic.
Scaner uses data from Twitter to do several tasks as:
- Rank most influential users in Twitter according to topics
- Find the network of an user
- Analyze data from tweets studying its impact or relevance.
To do so, Scaner provides an API REST to easily manage data and periodically calculate metrics of users and tweets.
Firstly you have to install Docker and Docker Compose. This can be easily installed with pip:
$ pip install docker-composeNow, clone the repository into your local system
$ git clone http://github.com/gsi-upm/scanerUse Docker Compose to build the application:
$ cd scaner
$ docker-compose buildThen, it is necessary to run OrientDB
$ ./populate_schema.shFinally, we run the application
$ docker-compose upScaner application it is now available on port 5000
For more information visit http://scaner.readthedocs.io/en/latest/
This development has been partially funded by the European Union through the MixedEmotions Project (project number H2020 655632), as part of the RIA ICT 15 Big data and Open Data Innovation and take-up programme.
