Mining tweets with R: Uncover the secrets spoken in the twitter universe

Twitter is currently ranked in the top 10 for most-visited website, and averaging on 500 million tweets a day. It is not just a microblogging outlet used by individuals and celebrities, but also for big commercial organisations, such as Telstra, NAB and Qantas, as a communication channel. However, few companies have deployed data analytics in this space due to the challenges in mining unstructured data. And hence, it is unclear what value can be achieved from mining twitter data. I will embark on the journey to explore some of the data mining techniques that can be applied on tweets to uncover potential gems for business or personal use.

Eu Jin Lok is a data analyst for iSelect, a graduate from Monash University with a Masters in Econometrics and has been using R for more than 3 years now both professionally and for causal purposes (eg- Kaggle). This will be his 2nd talk for the MelbURN group and in this talk, he will embark on the task of applying data mining techniques on tweeter feeds using a real example.