GitSentiment

Study based on Sentiment analysis of commit comments in GitHub: an empirical study

Requirements

• Python 2.x
• Virtualenv
• MongoDB
• SQLite3

Description of directories

docs

Holds the different documents that are related to our project.

emotionsStats

Holds the manipulation of our SQL table to find the paper's research questions.

repoAnalysis

Holds the analysis of repositories such as LINTing to answer our additional research question.

sentimentAnalysis

Holds the sentiment analysis module and the creation of the SQL table to carry out the rest of the project.

test

Holds our JSON objects for intermittent data changes.

utils

Various tools for processing of data.

Installation

Setting up the virtual environment

Creating and Activating

    $ virtualenv venv
    $ source venv/bin/activate

Deactivating (after executing program)

    $ deactivate

Installation Requirements

    $ pip install -r requirements.txt

Database Setup/Download (Not Required)

MSR 2014 Mining Challenge Dataset

• perform these operations within the main repo directory, it should create a dump directory

    $ wget http://ghtorrent-downloads.ewi.tudelft.nl/datasets/msr14-mongo.tar.gz
    $ tar zxvf msr14-mongo.tar.gz

MongoDB database dump (if wget command above doesn't work)

Run

    $ python gitSentiment.py

Other functionality

If you want to run the repoAnalysis, you must have the latest version of node, and you must install the JS linter via npm install -g standard --save-devsour. For all dependencies (assuming npm and pip on system), just run ./install.sh