From the course: NLP with Tidytext R
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Sentiment analysis with sentiments() - R Tutorial
From the course: NLP with Tidytext R
Sentiment analysis with sentiments()
- [Instructor] Sentiment analysis is a natural language processing tool used to determine the intent of a document. By attaching values to words, we can determine whether a document is intended to be negative or positive or angry or happy. Let's take a look at how tidytext implements sentiment analysis and let's take a look at why you might be concerned about how sentiment analysis operates. In line three, four, and five, I bring in the tidyverse and tidytext packages. Then in line eight is the sentiments command. And sentiments provides for us a list of words, you can see these down in a console, followed by a sentiment, in this case, negative. So if you look at line two, abnormal is ranked as negative. Line nine provides us with all of the sentiments available in this particular dictionary, and you'll notice that only negative and positive appear as sentiments in this particular dictionary. What you're seeing is…
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Inhalt
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How to think like tidytext1m 59s
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An example: Calculate the most popular terms in a document3m 10s
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Tokenizing with unnest_tokens()8m 19s
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Stopwords, punctuation, whitespace, and numbers6m 30s
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Stemming and lemmatization5m 35s
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Term frequency with bind_tf_idf()5m 54s
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Sentiment analysis with sentiments()4m 44s
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Parts of speech with parts_of_speech()4m 32s
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Import and export from other NLP packages2m 30s
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