Text mining with R
Text mining with R
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 32M | Lec: 15 | 91 MB
Genre: eLearning | Language: English
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 32M | Lec: 15 | 91 MB
Genre: eLearning | Language: English
Analyze twitter text using R
Have you always wanted to mine twitter data? Then this course is for you. This course presents example of text mining with R. Twitter text of @pycon and @udemy is used as the data to analyze. It starts by extracting text from Twitter. The extracted text is then transformed to a corpus and then a document-term matrix. After that, frequent words and associations are found from the matrix. A word cloud is used to present important words in documents.
There are three important packages used in the examples: twitteR, tm and wordcloud. Package twitteR provides access to Twitter data, tm provides functions for text mining, and wordcloud visualizes the result with a word cloud.
This course is meant for people who have basic knowledge of R and are interested in learning about text mining, in particular about how to mine data from Twitter. At the end of this course, you will be able to build term-document matrix and word clouds for any user on Twitter.
Text mining with R
