Chapter 11. Sentiment Analysis of Twitter Data

In this chapter we will see how to perform sentiment analysis over Twitter data. Initially, we introduce the Twitter API with Python. Then, we distinguish the basic elements of a sentiment classification. Finally, we present the Natural Language Toolkit (NLTK) to implement the tweets' sentiment analyzer.

In this chapter we will cover:

• The anatomy of Twitter data

• Using OAuth to access Twitter API

• Getting started with Twython:

  • Simple search/query

  • Working with timelines

  • Working with followers

  • Working with places and trends

• Sentiment classification:

  • Effective norms for English words

  • Text corpus

• Get started with Natural Language Toolkit (NLTK)

  • Bag of words

  • Naïve Bayes

  • Sentiment analysis of tweets

In Chapter 4, Text Classification, we presented a basic introduction to text classification. In this chapter, we will perform a sentiment analysis of tweets to rate the emotional value (positive or negative) using classification with Naive Bayes method.

Sentiment analysis...