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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

### Required packages - numpy - scipy - scikit-learn - Cython - h5py - python-louvain - [reveal-user-annotation](https://github.com/MKLab-ITI/reveal-user-annotation)

### Installation To install for all users on Unix/Linux:

python3.4 setup.py build sudo python3.4 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.

Project details


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Source Distribution

reveal-user-classification-0.1.17.tar.gz (19.5 kB view hashes)

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