Google Trends Data Mining Using R
- No prerequisites, previous exposure to R and windows work environment will be helpful..
- You will need access to R, Windows, Google account, Chrome.
Google Trends is a new tool in a Data Scientist or a Marketing Analyst's tool box. It provides data that could be quite useful when assessing trend in general public interest in a particular product or an array of products. Trends data essentially gives us a way to assess how often a particular search was performed on world's most popular search engine.
However, Google Trends only allows a simultaneous search of up to five terms, also it does not provide data through a dedicated API. This course describes two processes in R which could be employed to circumvent both of these issues. First process stitches together R and Windows batch system. Second, utilize gtrendsR package. In both case we set up an automated process.
The course begins by describing Google Trends data itself, and then various R functions relevant to build the automated solution. In the third section, we apply the knowledge from previous sections to build a complete end to end solution.
By the end of the course, we will better understand how R could be employed in more automated manner with minimum human involvement. Additionally, better appreciate the power of Google Trends data to provide a greater understanding of the way the world around us functions.
Who this course is for:
- Those wanting to retrieve and explore large amounts of Google Trends data.
- Students with beginner level of R understanding and those wanting to join course which is not typical beginner's curriculum. We will stay focused on using R to automate a software process.
- We will NOT deal with any statistics here!
I have played at the forefront of data analytics for the last 15 or so years. Until 2010, I worked at University of Southern California, Los Angeles as Assistant Professor and then moved to The Nielsen Company to join Analytics team focused in Social Media and Entertainment space. I am interested in using the power of Big Data to understand basic human behaviour when making a choice.
Apart from Data Science, my interests include Baseball, Cricket, and Hiking.