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Java for Data Science

You're reading from  Java for Data Science

Product type Book
Published in Jan 2017
Publisher Packt
ISBN-13 9781785280115
Pages 386 pages
Edition 1st Edition
Languages
Authors (2):
Richard M. Reese Richard M. Reese
Profile icon Richard M. Reese
Jennifer L. Reese Jennifer L. Reese
Profile icon Jennifer L. Reese
View More author details

Table of Contents (19) Chapters

Java for Data Science
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. Getting Started with Data Science 2. Data Acquisition 3. Data Cleaning 4. Data Visualization 5. Statistical Data Analysis Techniques 6. Machine Learning 7. Neural Networks 8. Deep Learning 9. Text Analysis 10. Visual and Audio Analysis 11. Mathematical and Parallel Techniques for Data Analysis 12. Bringing It All Together

Sentiment analysis


Sentiment analysis involves the evaluation and classification of words based on their context, meaning, and emotional implications. Typically, if we were to look up a word in a dictionary we will find a meaning or definition for the word but, taken out of the context of a sentence, we may not be able to ascribe detailed and precise meaning to the word.

For example, the word toast could be defined as simply a slice of heated and browned bread. But in the context of the sentence He's toast!, the meaning changes completely. Sentiment analysis seeks to derive meanings of words based on their context and usage.

It is important to note that advanced sentiment analysis will expand beyond simple positive or negative classification and ascribe detailed emotional meaning to words. It is far simpler to classify words as positive or negative but far more useful to classify them as happy, furious, indifferent, or anxious.

This type of analysis falls into the category of effective computing...

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