text mining

Text Mining, Web Scraping and Sentiment Analysis with R – Mining Twitter Data

Is the Text Mining, Web Scraping and Sentiment Analysis with R course for you?

  • Are you an advanced R user, looking to expand your R toolbox?
  • Are you interested in social media sentiment analysis?
  • Do you want to learn how you can get and use Twitter data for your R analysis?
  • Do you want to learn how you can systematically find related words (keywords) to a search term using Twitter and R?
  • Are you interested in creating visualizations like wordclouds out of text data?
  • Do you want to learn which R packages you can use for web scraping and text analysis purposes?

If YES came to your mind to some of those points – this course might be tailored towards your needs!

This course will teach you anything you need to know about how to handle social media data in R. We will use Twitter data as our example dataset.

During this course we will take a walk through the whole text analysis process of Twitter data.

At first you will learn which packages are available for social media analysis.

You will learn how to scrape social media (Twitter) data and get it into your R session.

After that we will filter, clean and structure our text corpus.

The next step is the visualization of the text data via wordclouds and dendrograms.

And in the last section we will do a whole sentiment analysis by using a common word lexicon.

All of those steps are accompanied by exercise sessions so that you can check if you can put the information to work.

According to the teaching principles of R Tutorials every section is enforced with exercises for a better learning experience. You can download the code pdf of every section to try the presented code on your own.

If you are not yet on an advanced level in R programming, we would highly recommend our R Level 1 course. The Level 1 course covers all the basic coding strategies that are essential for your day to day programming. R features like functions and apply are covered in the Level 1 course and are also needed for this course.

What are the requirements?

  • intermediate R knowledge is required (R Level 1 course)
  • R program ready on your computer
  • basic understanding of social media and web technologies

What am I going to get from this course?

  • Over 34 lectures and 3 hours of content!
  • use R for social media mining
  • get data from Twitter to do text analysis
  • perform web scraping tasks using the twitteR package
  • know which packages to use for web scraping
  • get R and Twitter connected
  • know how to perform a sentiment analysis in R
  • plot text data visualizations

What is the target audience?

  • everybody interested in social media analysis
  • everybody interested in using R for web scraping
  • everybody interested in sentiment analysis
  • everybody interested in text analysis
  • everybody interested in enlarging their R toolbox

What our students think

“This was pretty good. I knew very little about the scraping of Tweets so I found this valuable. I already knew a lot about Text Mining. I was very interested in sentiment analysis. The instructor’s presentation of it was good but I would have liked to have learned other methods of sentiment analysis such as the ones in the qdap and syuzhet packages.”

“This is a highly focused and well-designed class around Twitter and Sentiment analysis. The construction of the Breen sentiment scoring function is a nice takeaway. If you have never done Twitter or analysis of words, this is a good course in R to start with and build from.”

“Martin does a great job of teaching by example. While R is not the most complicated language out here, it has plenty of packages that are built for it. Martin has taken the topic of text mining, scraping, and sentiment analysis and shown how to accomplish these tasks through use of R. This is a growing area of study and this course will definitely show you what can be done. If you have any interest in this topic, the course will whet your appetite for more!”

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text mining

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