Sentiment analysis may be defined as a task performed on natural languages. Here, computations are performed on the sentences or words expressed in natural language to determine whether they express a positive, negative, or a neutral sentiment. Sentiment analysis is a subjective task, since it provides the information about the text being expressed. Sentiment analysis may be defined as a classification problem in which classification may be of two types—binary categorization (positive or negative) and multi-class categorization (positive, negative, or neutral). Sentiment analysis is also referred to as text sentiment analysis. It is a text mining approach in which we determine the sentiments or the emotions behind the text. When we combine sentiment analysis with topic mining, then it is referred to as topic-sentiment analysis. Sentiment analysis can be performed using a lexicon. The lexicon could be domain-specific or of a general purpose nature. Lexicon...
Mastering Natural Language Processing with Python
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Mastering Natural Language Processing with Python
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Overview of this book
<p>Natural Language Processing is one of the fields of computational linguistics and artificial intelligence that is concerned with human-computer interaction. It provides a seamless interaction between computers and human beings and gives computers the ability to understand human speech with the help of machine learning.</p>
<p>This book will give you expertise on how to employ various NLP tasks in Python, giving you an insight into the best practices when designing and building NLP-based applications using Python. It will help you become an expert in no time and assist you in creating your own NLP projects using NLTK.</p>
<p>You will sequentially be guided through applying machine learning tools to develop various models. We’ll give you clarity on how to create training data and how to implement major NLP applications such as Named Entity Recognition, Question Answering System, Discourse Analysis, Transliteration, Word Sense disambiguation, Information Retrieval, Sentiment Analysis, Text Summarization, and Anaphora Resolution.</p>
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Mastering Natural Language Processing with Python
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Table of Contents (17 chapters)
Mastering Natural Language Processing with Python
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Free Chapter
Working with Strings
Statistical Language Modeling
Morphology – Getting Our Feet Wet
Parts-of-Speech Tagging – Identifying Words
Parsing – Analyzing Training Data
Semantic Analysis – Meaning Matters
Sentiment Analysis – I Am Happy
Information Retrieval – Accessing Information
Discourse Analysis – Knowing Is Believing
Evaluation of NLP Systems – Analyzing Performance
Index
Customer Reviews