Follow the instructions below and write an essay that covers the following tasks. R script. R screenshot/s, your results and explanations should be included for each question in the essay. 1 Load Twitter Spam dataset into R studio, use ggplot function to make density plot of Tweets' number (column: no_tweets) to compare spam and non-spam. Clarify how you make the plot and what's your observation from the density plot. 2 Use ggplot function to make scatterplots to present the relation of posted tweets number (column: no_tweets) and the number of followers (column: no_follower), displaying spammer and non-spammer with different colours. Clarify how you make the plot and what's your observation from the scatter plot. 3 Add regression lines to the scatterplot generated in Step 2 for spammer and non-spammer separately. what's your observation from the regression lines? Compared with scatterplot only, what are the advantages of adding regression lines? Table 1. Account-based and Content-based Features Description Feature Name Description Account-based Features account age no follower no following no.userfavorites no lists no tweets no. retweets no tweetfavorites no hashtag no usermention no.urls no.char no.digits The age of an account # of followers # of followings #of favourites the user received # of lists in which the user is a member of #of tweets that has been posted by the user. Content-based Features # of times this tweet has been retweeted # of favourites this tweet received # of hashtags in this tweet # of times this tweet being mentioned #of URLs contained in this tweet # of characters in this tweet # of digits in this tweet