Email Datasets can be found here
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Updated
Dec 28, 2025 - Python
Email Datasets can be found here
A Person Of Interest identifier based on ENRON CORPUS data.
The code and data for "Are Large Pre-Trained Language Models Leaking Your Personal Information?" (Findings of EMNLP '22)
Fraud Detection by finding the Person of Interest (POI)
The fraud identification models were build using Python Scikit-learn machine-learning module.
CEREC and Seed corpus for coreference resolution for email threads taken from the Enron Corpus
[Incomplete] A chrome extension that tells you if a mail you're currently drafting is going to be classified as spam or not.
📩 Modeling the Enron dataset of emails using graphs
Enron Email Analysis
Natural Language Processing (NLP) and programmatic data extraction in large scale fraud investigations.
A project on Extract-Transform-Load (ETL) operations performed on the emails from the infamous enron corpus database.
📧 A data engineering exercise
Spam and No Spam text classification with Convolutional Neuronal Network and Word Embedding
LT2212 V20 Assignment 3: Same-author-classification via feed-forward neural networks: Transformed email text (Enron) into a machine readable representation and built a classifier that determines whether two texts are authored by the same person or not.
Identifying and cleaning the outliers of the Enron Dataset.
Machine learning algorithms applied to explore Enron email dataset and figure out patterns about people involved in the scandal.
This repository contains code for normalizing the Enron dataset.
The final project for the University of Malta unit Web Intelligence (ICS2205). The 60% component involved an individual analysis on a twitter dataset using NetworkX. The 40% component involves half of group task where an analysis was performed on the enron email dataset using NetworkX.
Identify Fraud from Enron Email
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