Using the Twitter API and a Python script or otherwise, search for up to 1500 recent tweets around a particular event or topic based hashtag. (Try to identify a hashtag that has a "small" number of participants (10s to 100s) who send tweets to each other at least some of the time. 2.	Write a Python routine that will loop through each of the search results, identify the distinct users who sent the tweet and a count of the number of tweets send by each of them in the sample you collected. 3.	Extend your program to print out (or save to a file) a sorted league table showing the top 10 tweeters, along with their rank position by tweet volume and a count of the number of tweets they sent. 4.	Visualise this data using datawrapper.de or a spreadsheet programme such as Google Sheets to produce a bar chart showing the top 10 tweeters along with the number of tweets each of them sent.  5.	Optional extension: Tweets that start with a Twitter ID may be thought of as "conversational", specifically tweets that are referred to one user by another who starts a tweet with that particular user's name. For each "conversational" tweet, extract who sent the tweet and to whom, and produce two more league tables: i)	showing an ordered ranking of who sent the most conversational tweets  ii)	 showing an ordered ranking of who received the most conversational tweets. 6.	Identify how many unique (sender,receiver) pairings there are in your sample (a weak measure of conversational diversity), and produce an ordered league table that displays how many times each conversational pairing was observed in the sampled dataset.