Predicting Brazilian court decisions

Repository of the paper entitled Predicting Brazilian court decisions.

Versions

• 2022 Full paper published at PeerJ Computer Science journal
• 2019-04-21 Technical Report @ Github
• 2019-04-20 Technical Report @ arXiv

Citation

• Lage-Freitas A, Allende-Cid H, Santana O, Oliveira-Lage L. 2022. Predicting Brazilian Court Decisions. PeerJ Computer Science 8:e904 https://doi.org/10.7717/peerj-cs.904

Methodology

We used this Python program for Steps 4, 5, 6, 7, 8, and 9 of our methodology. The Web scraper, regarding the Steps 1, 2, and 3 of our methodology, are under JusPredict (https://www.juspredict.com.br) Intellectual Property.

Data set

This data set has Ementa (summary) decisions from the Tribunal de Justiça de Alagoas (TJAL, the State Supreme Court of Alagoas (Brazil), and their metadata. The file format is CSV and its separator (delimiter) is "<=>".

Acknowledgments

• We thank the anonymous reviewers who provided significant and constructive critiques of this manuscript.
• André Lage-Freitas, Héctor Allende-Cid, and Orivaldo Santana are founders of the artificial intelligence startup JusPredict.
• Héctor Allende-Cid was funded by the Comisión Nacional de Investigación Científica y Tecnológica (CONICYT) under Grant No REDI170059.
• There was no additional external funding received for this study.

Reproducible Materials

Execution

python predicting-brazilian-court-decisions.py 

Requirements

• Python 3.7.7
• Source-code predicting-brazilian-court-decisions.py
• Data dataset.zip
• Cuda-based GPU (required only for Deep Learning models)
• Required packages:
  • absl-py==0.8.1 alembic==1.3.1 ase==3.21.1 asn1crypto==1.3.0 astor==0.8.0 async-generator==1.10 attrs==19.3.0 autovizwidget==0.13.1 backcall==0.1.0 beautifulsoup4==4.8.2 bert-serving-client==1.10.0 bert-serving-server==1.10.0 biterm==0.1.5 bleach==3.1.0 blinker==1.4 blis==0.2.4 boto==2.49.0 boto3==1.11.0 botocore==1.14.0 bs4==0.0.1 bz2file==0.98 celluloid==0.2.0 certifi==2019.11.28 certipy==0.1.3 cffi==1.13.2 chardet==3.0.4 cloudpickle==1.2.2 cryptography==2.8 cycler==0.10.0 cymem==2.0.2 Cython==0.29.14 cytoolz==0.9.0.1 dask==2.9.1 decorator==4.4.1 defusedxml==0.6.0 dill==0.2.9 docutils==0.15.2 entrypoints==0.3 es-core-news-sm==2.1.0 et-xmlfile==1.0.1 flags==0.0.1.2 funcy==1.14 future==0.18.2 gast==0.2.2 gensim==3.8.0 google-pasta==0.1.8 googledrivedownloader==0.4 GPUtil==1.4.0 grpcio==1.16.1 h5py==2.10.0 hdijupyterutils==0.12.9 idna==2.8 imageio==2.6.1 imbalanced-learn==0.6.2 imblearn==0.0 importlib-metadata==1.3.0 ipykernel==5.1.3 ipyparallel==6.2.4 ipython==7.13.0 ipython-genutils==0.2.0 ipywidgets==7.5.1 isodate==0.6.0 isort==4.3.21 jdcal==1.4.1 jedi==0.15.2 Jinja2==2.10.3 jmespath==0.9.4 joblib==0.14.1 json5==0.8.5 jsonschema==3.2.0 jupyter==1.0.0 jupyter-client==5.3.4 jupyter-console==6.0.0 jupyter-core==4.6.1 jupyter-lsp==0.8.0 jupyter-telemetry==0.0.5 jupyterhub==1.1.0 jupyterhub-systemdspawner==0.13 jupyterlab==2.1.2 jupyterlab-server==1.1.1 Keras==2.2.4 Keras-Applications==1.0.8 keras-contrib==2.0.8 Keras-Preprocessing==1.1.0 kiwisolver==1.1.0 langdetect==1.0.7 lazy-object-proxy==1.4.3 llvmlite==0.36.0 Mako==1.1.0 Markdown==3.1.1 MarkupSafe==1.1.1 mat4py==0.4.2 matplotlib==3.1.2 mccabe==0.6.1 mistune==0.8.4 mkl-fft==1.0.6 mkl-random==1.0.1 mock==3.0.5 more-itertools==8.0.2 mrcnn==0.2 msgpack==0.6.1 msgpack-numpy==0.4.3.2 murmurhash==1.0.2 nbconvert==5.6.1 nbformat==4.4.0 networkx==2.4 nltk==3.4.5 notebook==6.0.3 numba==0.53.1 numexpr==2.7.1 numpy==1.15.4 oauthlib==3.1.0 olefile==0.46 openpyxl==3.0.6 opt-einsum==3.1.0 packaging==20.0 pamela==1.0.0 pandas==0.25.3 pandocfilters==1.4.2 parso==0.5.2 patsy==0.5.1 pexpect==4.7.0 pickleshare==0.7.5 Pillow==7.0.0 plac==0.9.6 plotly==4.6.0 pluggy==0.13.1 preshed==2.0.1 prometheus-client==0.7.1 prompt-toolkit==2.0.10 protobuf==3.11.2 psycopg2==2.8.5 ptvsd==4.3.2 ptyprocess==0.6.0 py==1.8.1 pycparser==2.19 pycurl==7.43.0.3 pydocstyle==5.0.2 pydot==1.3.0 pydotplus==2.0.2 pyflakes==2.1.1 pygifsicle==1.0.1 Pygments==2.5.2 PyJWT==1.7.1 pykerberos==1.2.1 pyLDAvis==2.1.2 pymongo==3.9.0 pyOpenSSL==19.1.0 pyparsing==2.4.6 PyQt5==5.12.3 PyQt5-sip==4.19.18 PyQtWebEngine==5.12.1 pyrsistent==0.15.6 PySocks==1.7.1 pytest==5.3.4 python-dateutil==2.8.1 python-editor==1.0.4 python-json-logger==0.1.11 python-jsonrpc-server==0.3.4 python-louvain==0.15 pytz==2019.3 PyWavelets==1.1.1 PyYAML==5.2 pyzmq==18.1.0 qtconsole==4.6.0 rdflib==5.0.0 regex==2019.12.9 requests==2.22.0 requests-kerberos==0.12.0 retrying==1.3.3 ruamel.yaml==0.16.6 ruamel.yaml.clib==0.2.0 s3transfer==0.3.0 scikit-fuzzy==0.4.2 scikit-image==0.15.0 scikit-learn==0.22.2.post1 scipy==1.1.0 seaborn==0.9.0 Send2Trash==1.5.0 sentencepiece==0.1.85 six==1.13.0 smart-open==1.9.0 snowballstemmer==2.0.0 soupsieve==2.0 spacy==2.1.8 sparkmagic==0.13.1 SQLAlchemy==1.3.12 srsly==1.0.2 statsmodels==0.11.0 TBB==0.1 tensorboard==1.14.0 tensorflow==1.14.0 tensorflow-addons==0.8.3 tensorflow-estimator==1.14.0 tensorflow-hub==0.9.0 termcolor==1.1.0 terminado==0.8.3 testpath==0.4.4 thinc==7.0.8 toolz==0.10.0 torch-geometric==1.7.0 tornado==6.0.3 tqdm==4.41.1 traitlets==4.3.3 ujson==1.35 Unidecode==1.1.1 urllib3==1.25.7 wasabi==0.8.0 wcwidth==0.1.7 webencodings==0.5.1 Werkzeug==0.16.0 widgetsnbextension==3.5.1 wordcloud==1.6.0.post14+g1fc6868 wrapt==1.12.1 xgboost==0.90 xlrd==1.2.0 zipp==0.6.0