Does Taylor Swift Have a Big Reputation?

Twitter Scraping Using R

“Big Reputation, Big Reputation, Ooh you and me we’ve got Big Reputations”

Taylor Swift has just released her 6th studio album ‘Reputation’. The old Taylor is dead, and is her place is a new edgier Taylor, toughened from the years of media scrutiny, turbulent relationships and high profile celebrity feuds. As the title suggests, this is an album all about the contrast in how the world sees you to compared to who you really are and how a negative portrayal can affect your relationships. Whether you like the album or not (personally I love it), this post is not really about Taylor swift. This is about my first experience delving into the world of twitter scraping.

Twitter was created in 2006 and since then has rapidly grown into a world wide social network with around 330 million active users in 2017. Twitter along with other social media giants such as Facebook, youtube, linkedIn, Instragram etc., have revolutionised the way we share news and interact with both friends and celebrities. Every day we leave behind a trail of our virtual movements including comments, likes, networks of friends and even just pages we view. With so much data being produced every day, companies are eager to collect this data and use it to provide customer insight and improve products and services. For example, a company can search for tweets mentioning their name to see how they are being perceived by the public or they can analyse their followers to look for patterns and expand their presence online.  Accessing data in this way is often called social media mining.