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Word Cloud using R Programming

A word cloud is a visual representation of a collection of words.

Word clouds (also known as text clouds or tag clouds) work in a simple way: the more a specific word appears in a source of textual data (such as a speech, blog post, or database), the bigger and bolder it appears in the word cloud.

Benefits of Using Word Cloud Analysis

  1. Finding customer pain points --- and opportunities to connect.
  2. Finding customer pain points --- and opportunities to connect.
  3. Finding customer pain points --- and opportunities to connect.

Word Cloud using R Programming Tutorial Step by Step

I assume that you already have latest version of R and RStudio installed on your PC. Please do follow all the steps to understand how Word Cloud is build using R Programming and its packages.

Step 1: First of all, Download or Clone my Github Repo.

https://github.com/DineshThapaX/wordcloud_project

Step 2: my.R is the source file of the project.

Please install "tm" package on your RStudio using Console. That is essential for our project. You can also download it manually from packages section.

install.packages ("tm")

"tm" package in R is the Text Mining package. The "tm" package offers functionality for managing text documents, abstracts the process of document manipulation and eases the usage of heterogeneous text formats in R.

Step 3: Follow and read all the texts without skipping.

my.R is my source file. For your practice, please create your own source file named "test.R" in your working directory.

We will solve this problem in three major steps.

a. Preparing data for word

b. Displaying the Word Cloud

c. Enhancing the Word Cloud

a. Preparing data for word cloud

a1. Create a corpos object using VCorpus class.

First of all, Load "tm" package in your source code.

library("tm")

Creating a course_corpus object from Vcorpus class.

course_corpus = VCorpus(DirSource("//students.uce.ac.uk/filespace/mb20/tic/S23206188/DataMiningProjects/wordcloud_project/text-analytics/courses"))

To know more about the corpus, follow this:-

https://rdrr.io/rforge/tm/man/Corpus.html

In the above code, VCorpus creates a object and stores the content of my texts data from courses folder in the course_corpus variable.

In your case, please provide your own directory source.

a2. Convert texts data to lower case

course_corpus2 = tm_map(course_corpus, content_transformer(tolower))

The tm_map () function is used to remove unnecessary white space, to convert the text to lower case, to remove common stopwords like 'the', "we".

a3. Remove punctuations

course_corpus3 = tm_map(course_corpus2, removePunctuation)

a4. Remove stopwords

course_corpus4 = tm_map(course_corpus3, removeWords, stopwords())

a5. Generate TF-IDF matrix Term Document/Inverse Document Frequency(TF-IDF) is a powerful text analysis technique to find similar documents based their vector representations.

course_dtm <- DocumentTermMatrix(course_corpus4)

a6. Inspect to TF-IDF

inspect(course_dtm)

In R, the inspect() function is used to print the internal representation of an R object or the result of an expression. The inspect() function is also used to track the executed code lines of a function or method.

a7. Generate a frequency data frame

word_frequency <- sort(colSums(as.matrix(course_dtm)),decreasing=TRUE)
df_frequency<- data.frame(word = names(word_frequency),freq=word_frequency)

a8. Display the first few rows of the data

The head () function in R is used to display the first n rows or elements of a vector, matrix, table, data frame or function.

head(df_frequency)

b. Displaying the Word Cloud

b1. First of all, Install "wordcloud" package. Then, copy the below code step by step.

library("wordcloud")

b2. Simple wordcloud

wordcloud(df_frequency$word,df_frequency$freq)

b3. Displaying Top 10 words in wordcloud

wordcloud(df_frequency$word, df_frequency$freq, max.words=10, min.freq = 1)

c. Enhancing the Word Cloud

c1. Choose a specific font and order

wordcloud(df_frequency$word, df_frequency$freq, max.words=10, min.freq = 1,
          random.order=FALSE,family = "Helvatica", font = 3)

c2. Using a color palatte. First of all install "RColorBrewer" package.

library("RColorBrewer")

word_pal <- brewer.pal(10,"Dark2")

wordcloud(df_frequency$word,df_frequency$freq, max.words=20, min.freq = 1, random.order=FALSE, colors=word_pal, font = 3)

Congratulations! You have created an awesome project Word Cloud using R programming.