Create a python code that does the following below from the txt file called tweets.txt:Count the 10 words that appear most frequently in these tweets and print them in reverse order of frequencyReport what hashtags are used the tweets, including the number of times all hashtags appear in these tweets. (hint: you can use a regular expression to identify hashtags OR look for words which start with a #)Identifies how many of the tweets are retweets (retweets on twitter start with “RT @“) (hint: you can use a regular expression for this. What is the regular expression that matches the beginning of a string?)Identifies the 10 accounts which were retweeted the mostIdentify how many of these tweets are talking about the vaccine (you can use the keyword “vaccine” to look for tweets talking about the vaccine)Identifies the average sentiment among these tweetsExample of the output:************************Most frequent words************************covid, 204Fauci, 134the, 122…************************Hashtags used************************#covid, 221#vaccine, 144#cscw, 102…************************Retweets************************1,359 out of the 5,000 tweets are retweets************************Most Retweeted accounts************************bryan_kirschner, 304gvrkiasa, 292ingmase, 143…************************Vaccine tweets************************439 out of the 5,000 tweets talk about the vaccine************************Sentiment************************The average sentiment of the 5,000 tweets is 0.421

Python is a high-level computer programming language. It is used to develop software, websites, and scripts i.e automate a task and conduct data analysis. Python is easy to learn, and it is an easily human-readable language. Python language does not use curly brackets to delimit blocks like other programming languages. In the python language, semicolons are very rarely used. Semicolons are not compulsory, but we need to manage proper indentation in python programming language. The python programming language is used to perform operations on the txt file.The python program is as follows: Python program: import re #import regular expression. # open the txt file file = open("tweets.txt", "r") #open file in reading mode. # read the file text = file.read() # close the file file.close() # create an empty dictionaryword_dict = {} # create an empty listhashtags = [] # create variablesretweets = 0 #variable declaration.vaccine_tweets = 0sentiment_score = 0 # loop through the words in the text for word in text.split(): # if the word is already in the dictionary, increase its count if word in word_dict: word_dict[word] += 1 # otherwise, add it to the dictionary else: word_dict[word] = 1 # check if the word is a hashtag if word.startswith("#"): hashtags.append(word) # check if the tweet is a retweet if re.match("^RT @", word): retweets += 1 # check if the tweet is about the vaccine if word == "vaccine": vaccine_tweets += 1 # add sentiment score sentiment_score += 1 # sort the words by frequencysorted_words = sorted(word_dict.items(), key=lambda x:x[1], reverse=True) # print the 10 most frequent wordsprint("The 10 most frequent words in the tweets are:")for word in range(10): print(sorted_words[word][0]) # print the hashtagsprint("\nThe hashtags used in the tweets are:")for hashtag in hashtags: print(hashtag) # print the number of retweetsprint("\nThere are", retweets, "retweets in these tweets.") # print the number of vaccine tweetsprint("\nThere are", vaccine_tweets, "tweets about the vaccine.") # print the average sentiment scoreprint("\nThe average sentiment score among these tweets is", sentiment_score/len(text.split())) In the above code, the regular expression is imported. The program opens the tweets.txt file in reading mode. In the program, an empty dictionary and an empty list is created to store the word_dict and Hashtag. The program checks all the words in the tweets.txt file and if the word already exists in the dictionary then increase the count otherwise add a word in the dictionary. If the word starts with the # then add it to the hashtag. if the word starts with RT, @ then add it to the to retweet. If the word is equal to the vaccine, then it checks the tweet about the vaccine. Print all the operations with their numbers. Tweets.txt file contents are as follows: covid, 204Fauci, 134the, 122Most frequent words************************covid, 204Fauci, 134the, 122… ************************Hashtags used************************#covid, 221#vaccine, 144#cscw, 102… ************************Retweets************************1,359 out of the 5,000 tweets are retweets ************************Most Retweeted accounts************************bryan_kirschner, 304gvrkiasa, 292ingmase, 143… ************************Vaccine tweets************************439 out of the 5,000 tweets talk about the vaccine ************************Sentiment************************The average sentiment of the 5,000 tweets is 0.421 Review time left: 05:38AcceptDeclineThis is a PRIMARY question Output: The python program is successfully developed. The program reads the tweets.txt file and displays the output.

Answered: Create a python code that does the…

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Create a python code that does the following below from the txt file called tweets.txt:

Count the 10 words that appear most frequently in these tweets and print them in reverse order of frequency
Report what hashtags are used the tweets, including the number of times all hashtags appear in these tweets. (hint: you can use a regular expression to identify hashtags OR look for words which start with a #)
Identifies how many of the tweets are retweets (retweets on twitter start with “RT @“) (hint: you can use a regular expression for this. What is the regular expression that matches the beginning of a string?)
Identifies the 10 accounts which were retweeted the most
Identify how many of these tweets are talking about the vaccine (you can use the keyword “vaccine” to look for tweets talking about the vaccine)
Identifies the average sentiment among these tweets

Example of the output:

************************
Most frequent words
************************
covid, 204
Fauci, 134
the, 122
…

************************
Hashtags used
************************
#covid, 221
#vaccine, 144
#cscw, 102
…

************************
Retweets
************************
1,359 out of the 5,000 tweets are retweets

************************
Most Retweeted accounts
************************
bryan_kirschner, 304
gvrkiasa, 292
ingmase, 143
…

************************
Vaccine tweets
************************
439 out of the 5,000 tweets talk about the vaccine

************************
Sentiment
************************
The average sentiment of the 5,000 tweets is 0.421

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