Discovering sentiment analysis

In this recipe, we will use two simple tools for labeling a sentence as having positive or negative sentiment. The first tool is the NLTK Vader sentiment analyzer, and the second one uses the textblob package.

Getting ready

We will need the nltk and textblob packages for this recipe. If you haven't already installed them, install them using these commands:

pip install nltk
pip install textblob

In addition to this, you will need to run the following from Python the first time you use the Vader sentiment analyzer:

>> import nltk
>>nltk.download('vader_lexicon')

How to do it…

We will define two functions: one will do sentiment analysis using NLTK, and the other using TextBlob.

Your steps should be formatted like so:

1. Import the packages:

   from textblob import TextBlob
   from nltk.sentiment.vader import SentimentIntensityAnalyzer

2. Define the sentences list:

   sentences = ["I love going to school...