Twitter is one of the widely used social media platforms. Many a times, we see strong discussion on Twitter about someone’s opinion that sometimes results in a collection of negative tweets. For gauging whether the kind of tweets are positive, negative or have a neutral sentiment, we can use this simple Twitter Sentiment Analysis Engine. Sentiment analysis is a task of natural language processing. Various social media platforms monitor the sentiments of those engaged in a discussion using such sentiment analysis engines. For the purpose of this project, I have used a Kaggle dataset about a long discussion within a group of users on Twitter. Our task was to identify how many tweets are negative and positive so that we can give a conclusion.
Libraries and modules used:
- Pandas
- NLTK
- Stopwords
- Stemmer (SnowballStemmer)
- Re (regularExpression)