Performs user classification into labels using a set of seed Twitter users with known labels andthe structure of the interaction network between them.
Project description
Performs user classification into labels using a set of seed Twitter users with known labels and the structure of the interaction network between them.
Features
Graph-based, multi-label user classification platform.
Implementation of the ARCTE (Absorbing Regularized Commute Times Embedding) algorithm for graph-based feature extraction.
Both python vanilla and cython-optimized versions.
Implementation of other feature extraction methods for graphs (Laplacian Eigenmaps, Louvain, MROC).
Evaluation score and time benchmarks.
Install
To install for all users on Unix/Linux:
python setup.py build sudo python setup.py install
Alternatively:
pip install reveal-user-classification
Reveal-FP7 Integration
There is one console entry point:
user_network_profile_classifier assessment_id
where assessment_id is the address of a MongoDB instance.
### Configuration The configuration of the [reveal-user-annotation](https://github.com/MKLab-ITI/reveal-user-annotation) project is required. Follow the README instructions.
Experiments
(Section under construction.)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Hashes for reveal-user-classification-0.1.16.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9475278da00fae4942aecb33f6da517dd1042d318aa5f4a0688e2d7464bfbde6 |
|
MD5 | c59ca214d7ed1102de3f29192a3a1342 |
|
BLAKE2b-256 | feb15b23bbe1705b1dd7e8900a8fe616aee68f3f7ccb78861444a02561a358f1 |