Skip to content
An email semantic and sentiment analysis tool for company complaints and general labeling.
Python
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
__pycache__
.gitignore
README.md
analyzer.py
demo-video.txt
main.py
module_manager.py
timesheet.txt

README.md

Labely - 15-112 Term Project, Carnegie Mellon University

Labely is an email labeling and analysis tool for company complaints. This program helps business owners better understand common themes in emails, including key words (labels), important content, sentiment, and interconnections.

  • Author: Bennett Huffman
  • Mentor: Kusha Maharshi
  • Instructors: Kelly Rivers

Dependencies

Running Labely

  1. Download the project as a ZIP file.
  2. Select an exported CSV file of the emails you want to analyze from Gmail (may require converting from MBOX to CSV) and place it in the 'data' folder. Sample CSV files of emails can be downloaded here.
  3. Run the "main.py" file to begin. Press help for instructions.

Video

Check out the demo!

Features (toggle-able)

  • Email labeling and graphical visualization
  • Word frequency distribution and graphical visualization
  • Summarization of most important content in emails (only viewable in CSV export)
  • Sentiment analysis and graphical visualization over time
  • CSV Export (includes all selected features in analysis)

Navigation

  • To receive instructions, click on the help screen in the top right corner.
You can’t perform that action at this time.