Automate the case review on legal case documents and find the most critical cases using network analysis

Related tags

Data Visualizationpythonlexical-analysisnetwork-analysisigraphpdfminerpdf-parser
Overview

Automation on Legal Court Cases Review

This project is to automate the case review on legal case documents and find the most critical cases using network analysis.

Short write-up

Affiliation: Institute for Social and Economic Research and Policy, Columbia University

Project Information:

Keywords: Automation, PDF parse, String Extraction, Network Analysis

Software:

  • Python : pdfminer, LexNLP, nltk sklearn
  • R: igraph

Scope:

  1. Parse court documents, extract citations from raw text.
  2. Build citation network, identify important cases in the network.
  3. Extract judge's opinion text and meta information including opinion author, court, decision.
  4. Model training to predict court decision based on opinion text.

Polit Study on 159 Legal Court Documents (in pilot_159 folder)

1. Process PDF documents using Python

Ipython Notebook Description
1.Extraction by LexNLP.ipynb Extract meta inforation use LexNLP package.
2.Layer Analysis on Sigle File. ipynb Use pdfminer to extract the raw text and the paragraph segamentation in the PDF document.
3.Patent Position by Layer.ipynb Identify the position of patent number in extracted layers from PDF.
4.Opinion and Author by Layer.ipynb Extract opinion text, author, decisions from the layers list.
5.Wrap up to Meta Data.ipynb Store extracted meta data to .json or .csv
6.Visualize citation frequency.ipynb Bar plot of the citation frequencies

2. Data: Parse PDF documents via Python

These datasets are NOT included in this public repository for intellectual property and privacy concern

File
pdf2text159.json A dictionary of 3 list: file_name, raw_text, layers.
cite_edge159.csv Edge list of citation network
cite_node159.csv Meta information of each case: case_number, court, dates
reference_extract.csv cited cases in a list for every case, untidy format for analysis
citation159.csv file citation pair, tidy format for calculation
regulation159.csv file regulation pair, tidy format for calculation

3. Analyze and Visualize using R

File
Calculate Citation Frequency.Rmd Analyze reference_extract.csv
Citation Network.Rmd Analyze cite_edge159

4. Visulization Chart Sample

Citation Frequencycase_freq

Citation Networkcitation_net

Network Visulization and Predictive Modeling on 854 Legal Court Cases (in Extraction_Modelling folder)

1. Extract opinion and meta information from raw text data

.ipynb notebook Description
Full Dataset Merge.ipynb Merge the 854 cases dataset
Edge and Node List.ipynb Create edge and node list
Full Extractions.ipynb Extract author, judge panel, opinion text
Clean Opinion Text.ipynb Remove references and special characters in opinion text

2. Datasets

These datasets are NOT included in this public repository for intellectual property and privacy concern

Dataset Description
amy_cases.json large dictionary {file name: raw text} for 854 cases, from Lilian's PDF parsing
full_name_text.json convert amy_cases.json key value pair to two list: file_name, raw_text
cite_edge.csv edge list of citation
cite_node.csv node list contains case_code, case_name, court_from, court_type
extraction854.csv full extractions include case_code, case_name, court_from, court_type, result, author, judge_panel
decision_text.json json file include author, decision(result of the case), opinion (opinion text), cleaned_text (cleaned opinion text)
cleaned_text.csv csv file contains allt the cleaned text
predict_data.csv cleaned dataset for NLP modeling predict court decision

3. Visulization using R

R markdown file
Full Network Graph.Rmd draw the full citation network
Citation Betwwen Nodes.Rmd draw citation between all the available cases
Clean Data For Predictive Modelling.rmd clean text data for predictive modeling

Interactive Graph

Play with Interactive Graph

Full Citation Network (all cases and cited cases)

Citation Between Available Cases

4. Predictive Modeling using Python

ipynb notebook
NLP Predictive Modeling.ipynb Try different preprocessing, and build a logistic regression to predict court decision.

Visulization of the Bi-gram (words) with the strongest coefficient

Bigram

Owner
Yi Yin
Tech & Business Alignment @ Wolfram Research, Social Sciences Research @ Columbia University
Yi Yin
GitHub Repository
flask extension for integration with the awesome pydantic package

Flask-Pydantic Flask extension for integration of the awesome pydantic package with Flask. Installation python3 -m pip install Flask-Pydantic Basics v

249 Jan 06, 2023
A simple interpreted language for creating basic mathematical graphs.

graphr Introduction graphr is a small language written to create basic mathematical graphs. It is an interpreted language written in python and essent

2 Dec 26, 2021
Painlessly create beautiful matplotlib plots.

Announcement Thank you to everyone who has used prettyplotlib and made it what it is today! Unfortunately, I no longer have the bandwidth to maintain

Olga Botvinnik 1.6k Jan 06, 2023
Smoking Simulation is an app to simulate the spreading of smokers and non-smokers, their interactions and population during certain amount of time.

Smoking Simulation is an app to simulate the spreading of smokers and non-smokers, their interactions and population during certain

Bohdan Ruban 5 Nov 08, 2022
This is my favourite function - the Rastrigin function.

This is my favourite function - the Rastrigin function. What sparked my curiosity and interest in the function was its complexity in terms of many local optimum points, which makes it particularly in

1 Dec 27, 2021
These data visualizations were created as homework for my CS40 class. I hope you enjoy!

Data Visualizations These data visualizations were created as homework for my CS40 class. I hope you enjoy! Nobel Laureates by their Country of Birth

9 Sep 02, 2022
Seismic Waveform Inversion Toolbox-1.0

Seismic Waveform Inversion Toolbox (SWIT-1.0)

Haipeng Li 98 Dec 29, 2022
Blender addon that creates a temporary window of any type from the 3D View.

CreateTempWindow2.8 Blender addon that creates a temporary window of any type from the 3D View. Features Can the following window types: 3D View Graph

3 Nov 27, 2022
Tools for writing, submitting, debugging, and monitoring Storm topologies in pure Python

Petrel Tools for writing, submitting, debugging, and monitoring Storm topologies in pure Python. NOTE: The base Storm package provides storm.py, which

AirSage 247 Dec 18, 2021
Declarative statistical visualization library for Python

Altair http://altair-viz.github.io Altair is a declarative statistical visualization library for Python. With Altair, you can spend more time understa

Altair 8k Jan 05, 2023
Epagneul is a tool to visualize and investigate windows event logs

epagneul Epagneul is a tool to visualize and investigate windows event logs. Dep

jurelou 190 Dec 13, 2022
Design your own matplotlib stylefile interactively

Tired of playing with font sizes and other matplotlib parameters every time you start a new project or write a new plotting function? Want all you plots have the same style? Use matplotlib configurat

yobi byte 207 Dec 08, 2022
clock_plot provides a simple way to visualize timeseries data, mapping 24 hours onto the 360 degrees of a polar plot

clock_plot clock_plot provides a simple way to visualize timeseries data mapping 24 hours onto the 360 degrees of a polar plot. For usage, please see

12 Aug 24, 2022
Python toolkit for defining+simulating+visualizing+analyzing attractors, dynamical systems, iterated function systems, roulette curves, and more

Attractors A small module that provides functions and classes for very efficient simulation and rendering of iterated function systems; dynamical syst

1 Aug 04, 2021
Leyna's Visualizing Data With Python

Leyna's Visualizing Data Below is information on the number of bilingual students in three school districts in Massachusetts. You will also find infor

11 Oct 28, 2021
Automatically generate GitHub activity!

Commit Bot Automatically generate GitHub activity! We've all wanted to be the developer that commits every day, but that requires a lot of work. Let's

Ricky 4 Jun 07, 2022
PanGraphViewer -- show panenome graph in an easy way

PanGraphViewer -- show panenome graph in an easy way Table of Contents Versions and dependences Desktop-based panGraphViewer Library installation for

16 Dec 17, 2022
A GUI for Pandas DataFrames

PandasGUI A GUI for analyzing Pandas DataFrames. Demo Installation Install latest release from PyPi: pip install pandasgui Install directly from Githu

Adam 2.8k Jan 03, 2023
LabGraph is a a Python-first framework used to build sophisticated research systems with real-time streaming, graph API, and parallelism.

LabGraph is a a Python-first framework used to build sophisticated research systems with real-time streaming, graph API, and parallelism.

MLH Fellowship 7 Oct 05, 2022
Pyan3 - Offline call graph generator for Python 3

Pyan takes one or more Python source files, performs a (rather superficial) static analysis, and constructs a directed graph of the objects in the combined source, and how they define or use each oth

Juha Jeronen 235 Jan 02, 2023