content-analysis-backend

1- Install requirements: pip install -r requirements.txt

install the project: ` bash install.sh `

extract features: ` bash feature_extractor.sh `

run experiments on classical models: ` bash classical_experiments.sh `

run experiments on transformers: ` bash neural_experiments.sh `

This resposiory contains source code of content analysis module which assigns credibility score of given tweet.

• Free software: MIT license
• Documentation: https://content-analysis-backend.readthedocs.io.

Features

• TODO

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

Acknowledgments

Credibility features Olteanu et al [2013]:

@inproceedings{DBLP:conf/ecir/OlteanuPLA13,

author = {Alexandra Olteanu and

Stanislav Peshterliev and Xin Liu and Karl Aberer},

title = {Web Credibility: Features Exploration and Credibility Prediction}, booktitle = {{ECIR}}, series = {Lecture Notes in Computer Science}, volume = {7814}, pages = {557--568}, publisher = {Springer}, year = {2013}

}

Readability metrics:

https://github.com/andreasvc/readability

This work is sponsored by EU Project Horizon 2020 [CoInform](https://coinform.eu/)