Sentiment Analysis in Scala with Stanford CoreNLP


So far in this series, we have looked at finatra and sbt open-source Scala projects. This week I decided to learn Stanford CoreNLP library for performing sentiment analysis of unstructured text in Scala.

Sentiment analysis or opinion mining is a field that uses natural language processing to analyze sentiments in a given text. It has applications in many domains ranging from marketing to customer service. Few years back, I wrote a simple Java application using Naive Bayes classifier to determine whether people liked a movie or not based on sentiment analysis of tweets about a movie.

From the Stanford CoreNLP website,

Stanford CoreNLP provides a set of natural language analysis tools. It can give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize dates, times, and numeric quantities, and mark up the structure of sentences in terms of phrases and word dependencies, indicate which noun phrases refer to the same entities, indicate sentiment, extract open-class relations between mentions, etc.

You can read full blog here https://github.com/shekhargulati/52-technologies-in-2016/blob/master/03-stanford-corenlp/README.md

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