Java: Data Science Made Easy

Extracting data for a sentiment analysis model

In Chapter 9, Text Analysis, we used DL4J to perform sentiment analysis. We will use LingPipe in this example as an alternative to our previous approach. Because we want to classify Twitter data, we chose a dataset with pre-classified tweets, available at http://thinknook.com/wp-content/uploads/2012/09/Sentiment-Analysis-Dataset.zip. We must complete a one-time process of extracting this data into a format we can use with our model before we continue with our application development.

This dataset exists in a large .csv file with one tweet and classification per line. The tweets are classified as either 0 (negative) or 1 (positive). The following is an example of one line of this data file: