The program scrapes most recent tweets (posted in the last 7 days) that include a specific keyword . Tweets are then cleaned from links and special characters and duplicates are removed. Afterwards, sentiment analysis is performed using VADER-software.
pip install -r requirements.txt
export TWITTER_BEARER_TOKEN=<insert your bearer token>
# to download tweets posted in last 7 days with specified keyword:
./scrape.py
# to perform sentiment analysis:
./analysis.py
The following results are produced:
Hutto, C.J. & Gilbert, E.E. (2014). VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text. Eighth International Conference on Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014.