Quantitative Text Analysis and Scaling in R

提供方
Coursera Project Network
在此指導項目中,您將:

Run an unsupervised document scaling model Plot the output of the unsupervised scaling model

Clock1 hour
Beginner初級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

By the end of this project, you will learn about the concept of document scaling in textual analysis in R. You will know how to load and pre-process a data set of text documents by converting the data set into a corpus and document feature matrix. You will know how to run an unsupervised document scaling model and explore and plot the scaling outcome.

您要培養的技能

  • Text Analysis
  • Document Scaling
  • Unsupervised Learning
  • Data Visualization (DataViz)
  • Text Corpus

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Load textual data into R and turn it into a corpus object and understand the concept of document scaling in textual analysis

  2. Extract meta-data from text document filenames and subset the data frame to exclude unwanted data

  3. Tokenize and clean the dataset and convert the data into a document feature matrix

  4. Run an unsupervised document scaling model and explore the output

  5. Plot the output of the unsupervised scaling model

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

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常見問題

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