curioustauseef / tweet-sentiment-scores

Scripts for capturing tweets, creating data dictionary, processing & scoring tweet sentiments

Tweet Sentiment Analysis

Introduction

Scripts for capturing tweets, creating sentiment dictionary, processing & scoring tweet sentiments, written in Python. These scripts were written to facilitate the clustering of tweet length & sentiment scores in this research paper.

Twitter app authentication credentials are required for use of get_tweets.py. Acquire these here.

Inspiration for some of this material comes from Bill Howe and his Coursera course, Introduction to Data Science.

Description

get_tweets.py

• Captures tweets from Twitter stream
• Requires keys and secrets in order to successfully run

build_dict.py

• Takes existing sentiment dictionary as list of seed words
• Builds new dictionary of unscored tweet words based on tweet mean score of scored existing words

process_tweets.py

• Scores the tweets word-by-word based on crafted sentiment dictionary created with build_dict.py

extract_text.py

• Extracts the tweet text from the tweet JSON document, optionally saves to file

Usage

The research paper cited above provides detailed explanation and use case examples for utilizing these scripts.

Requirements

Python (tested with 2.7.7)

Installation

No installation; just download and run scripts

# get_tweets.py
python get_tweets.py > <capture_filename>

# build_dict.py
python build_dict.py <sentiment_file> <tweet_file> > <newsent_filename>

# process_tweets.py
python process_tweets.py <sentiment_file> <tweet_file>

# extract_text.py
python extract_tweets.py <tweet_file> > <output_file>

Getting Help

The code is fairly simple and should be easy to follow.

If you require an introduction to sentiment analysis, check here.

Author

Matt Mayo

License

This software is made available under the MIT License