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.
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
The research paper cited above provides detailed explanation and use case examples for utilizing these scripts.
Python (tested with 2.7.7)
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>The code is fairly simple and should be easy to follow.
If you require an introduction to sentiment analysis, check here.
This software is made available under the MIT License