Introduction to Sentiment Analysis in R with quanteda

von
Coursera Project Network
In diesem angeleitetes Projekt werden Sie:

Run your first generic and targeted sentiment analyses using a dataset of US presidential concession speeches.

Visualize sentiment analysis results over time in a plot while stratifying by an additional variable

Clock2 hours
BeginnerAnfänger
CloudKein Download erforderlich
VideoVideo auf geteiltem Bildschirm
Comment DotsEnglisch
LaptopNur Desktop

In this guided project, you will learn how to import textual data stored in raw text files into R, turn these files into a corpus (a collection of textual documents), and tokenize the text all using the R software package quanteda. You will then learn how to check for words with positive or negative sentiment within the text, and how to plot the proportion of use for these words over time, while stratifying by a third variable. You will also learn how to carry out a targeted sentiment analysis by looking for words with a positive or negative sentiment that are adjacent to relevant keywords or phrases, and how to compare the results of a targeted sentiment analysis with the results of a generic analysis.

Kompetenzen, die Sie erwerben werden

  • statistical programming
  • Statistical Classification
  • Sentiment Analysis
  • Text Corpus
  • Rstudio

Schritt für Schritt lernen

In einem Video, das auf einer Hälfte Ihres Arbeitsbereichs abgespielt wird, führt Sie Ihr Dozent durch diese Schritte:

  1. Load text documents into R studio, convert a number of text documents into a corpus, and extract data from text document file names and add them to a new column in a dataframe. 

  2. Split up a text document corpus into tokens, or individual words and punctuations. Check for words in the data that have positive or negative sentiment using the Sentiment Dictionary. 

  3. Plot the proportion of positive and negative words over time while stratifying by a third variable. 

  4. Carry out a targeted sentiment analysis by looking for words with a positive or negative sentiment that are adjacent to relevant keywords.

  5. Compare the sentiment for both generic and targeted sentiment analyses while stratifying by a third variable, plotting the results over time.

Ablauf angeleiteter Projekte

Ihr Arbeitsbereich ist ein Cloud-Desktop direkt in Ihrem Browser, kein Download erforderlich

Ihr Dozent leitet Sie in einem Video mit geteiltem Bildschirm Schritt für Schritt an.

Häufig gestellte Fragen

Häufig gestellte Fragen

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