Need help with a python program. Please follow instructions provided in assignmnet. Part C: Sentiment Analysis of Unlabelled ReviewsOnce Part B is complete, save your program into a new file so that you can modify it for Part C.Now, after creating and filling in the dictionary in Part A, open a new file containing unlabelledmovie reviews (unlabelledReviews.txt). The file will contain one movie review per line.Read in this file one line at a time, and calculate the rating for that line using the dictionary youcreated in Part A. The rating for each unlabelled review should be calculated as the averagerating of each word in that review (which you already know how to get from Part B, right?)For each review in this new file, print out:1. The review itself,2. The rating for that review to 1 decimal place, and3. Whether that review is considered POSITIVE, NEUTRAL, or NEGATIVE:Reviews with a rating greater than 2 are POSITIVEReviews with a rating equal to 2 are NEUTRALReviews with a rating less than 2 are NEGATIVEHint: When debugging your code, it will be helpful to print out each word in the new review andthe word's rating – so you can make sure that everything is working correctly. Then removethose print statements to get the final output, as below.Example output for two unlabelled movie reviews from a file:(Note: the file has more than 2 unlabelled movie reviews, and your program must process all ofthem)The movie review was:"You could hate it for the same reasonThis review is rated at 1.9 which is NEGATIVE.The movie review was:"The performances areThis review is rated at 2.2 which is POSITIVE.an absolute joyEnd of Processing.Requirements and Development notes:You do not need to ask the user for the filenames in Q2, you can "hardcode" the filenames into your program.Sample files are available on UM Learn.You can assume that the Grader will put the files to read in into the same directory asyour code when marking.program should display output in the format shown above.Your Question 2: Movie ReviewsSentiment Analysis is a problem within the field of Artificial Intelligence which seeks todetermine the general attitude of a writer given some text they have written. For instance, wewould like the program to recognize that the text "My favourite film all year" is a positivestatement while “A giant waste of time" is negative.One algorithm that we can use for this is to assign a number to each word based on how positiveor negative that word is, and then score the statement based on the values of the words. But, howdo we come up with our word scores in the first place?That's what we will do in this assignment. You are going to search through a file containingmovie reviews from the Rotten Tomatoes website which have both a numeric score as well astext. Your program will use this to learn which words are positive and which are negative. Thefile is called movieReviews.txt and is available on UM Learn.Notice that each review starts with a number 0 through 4 with the following meaning:0: negative1: somewhat negative2: neutral3: somewhat positive4: positiveYou are going to write a program that determines the score for each word in this file, and thenuses those word scores to decide if an unlabelled movie review is positive, negative, or neutral.Part A: Learning from Labelled Movie ReviewsTo begin, your program must compute the average sentiment score for each of the words in themovieReviews.txt file. Download the text file and save it in the same folder where yourprogram will be. Then write a program to do the following:Set up a new, empty dictionary.Iterate over every review in the text file (there is one review per line).Examine every word in every review within the file.If the word is not yet in your dictionary:o Add a new entry into your dictionary for that word. The word itself is the key, andthe value to store at this key is a list that contains two items: the sentiment scoreand the number 1 (meaning that you've seen this word 1 time).Otherwise (if the word is already in your dictionary):o Add the new sentiment score to the score that is already stored in the list, ando Increase the number of times that you have seen this word.For example, if the file contained only two reviews:4 It was great1 It was terrible3Then we would have the following key-value pairs in the dictionary:ValueKeyit[5, 2][5, 2][4, 1][1, 1]wasgreatterribleThere is no console output for Part A.What is a word? When designing a program like this, you need to make sure that you and theprogram's end users agree on what counts as a unique word. For this assignment:• Ignore capitalization: "And" and "and" should be counted as the same word.Do not worry about punctuation, symbols, or numbers within the review text - you do notneed to remove these. Just put everything you find into your dictionary. Your dictionarywill have entries that are just symbols (ex. "." or ",") and also entries that are numbers.• Make sure strip out all whitespace from each word. For example, you should not havewords in your dictionary that contain a space, tab character (" "), or newline (“
").Part B: Creating Word ScoresAfter your dictionary has been created and filled in Part A, ask the user to enter a word in theconsole.If that word exists in the dictionary, print out the number of times that word occurred in themovie review file and the average rating for that word. The average rating is the total scoredivided by the number of times that word occurred in the movie review file.Imagine our movie review file contains the same two reviews from Part A.Here are 3 example sessions (user input in blue):Enter a word: Great'great' appears 1 time(s) and has an average rating of 4.End of Processing.Enter a word: it'it' appears 2 time(s) and has an average rating of 2.5.End of Processing.Enter a word: haberdashery'haberdashery' does not appear in any movie reviews.End of Processing.4

Question

Need help with a python program. Please follow instructions provided in assignmnet. Part C: Sentiment Analysis of Unlabelled ReviewsOnce Part B is complete, save your program into a new file so that you can modify it for Part C.Now, after creating and filling in the dictionary in Part A, open a new file containing unlabelledmovie reviews (unlabelledReviews.txt). The file will contain one movie review per line.Read in this file one line at a time, and calculate the rating for that line using the dictionary youcreated in Part A. The rating for each unlabelled review should be calculated as the averagerating of each word in that review (which you already know how to get from Part B, right?)For each review in this new file, print out:1. The review itself,2. The rating for that review to 1 decimal place, and3. Whether that review is considered POSITIVE, NEUTRAL, or NEGATIVE:Reviews with a rating greater than 2 are POSITIVEReviews with a rating equal to 2 are NEUTRALReviews with a rating less than 2 are NEGATIVEHint: When debugging your code, it will be helpful to print out each word in the new review andthe word's rating – so you can make sure that everything is working correctly. Then removethose print statements to get the final output, as below.Example output for two unlabelled movie reviews from a file:(Note: the file has more than 2 unlabelled movie reviews, and your program must process all ofthem)The movie review was:&#34;You could hate it for the same reasonThis review is rated at 1.9 which is NEGATIVE.The movie review was:&#34;The performances areThis review is rated at 2.2 which is POSITIVE.an absolute joyEnd of Processing.Requirements and Development notes:You do not need to ask the user for the filenames in Q2, you can &#34;hardcode&#34; the filenames into your program.Sample files are available on UM Learn.You can assume that the Grader will put the files to read in into the same directory asyour code when marking.program should display output in the format shown above.Your Question 2: Movie ReviewsSentiment Analysis is a problem within the field of Artificial Intelligence which seeks todetermine the general attitude of a writer given some text they have written. For instance, wewould like the program to recognize that the text &#34;My favourite film all year&#34; is a positivestatement while “A giant waste of time&#34; is negative.One algorithm that we can use for this is to assign a number to each word based on how positiveor negative that word is, and then score the statement based on the values of the words. But, howdo we come up with our word scores in the first place?That's what we will do in this assignment. You are going to search through a file containingmovie reviews from the Rotten Tomatoes website which have both a numeric score as well astext. Your program will use this to learn which words are positive and which are negative. Thefile is called movieReviews.txt and is available on UM Learn.Notice that each review starts with a number 0 through 4 with the following meaning:0: negative1: somewhat negative2: neutral3: somewhat positive4: positiveYou are going to write a program that determines the score for each word in this file, and thenuses those word scores to decide if an unlabelled movie review is positive, negative, or neutral.Part A: Learning from Labelled Movie ReviewsTo begin, your program must compute the average sentiment score for each of the words in themovieReviews.txt file. Download the text file and save it in the same folder where yourprogram will be. Then write a program to do the following:Set up a new, empty dictionary.Iterate over every review in the text file (there is one review per line).Examine every word in every review within the file.If the word is not yet in your dictionary:o Add a new entry into your dictionary for that word. The word itself is the key, andthe value to store at this key is a list that contains two items: the sentiment scoreand the number 1 (meaning that you've seen this word 1 time).Otherwise (if the word is already in your dictionary):o Add the new sentiment score to the score that is already stored in the list, ando Increase the number of times that you have seen this word.For example, if the file contained only two reviews:4 It was great1 It was terrible3Then we would have the following key-value pairs in the dictionary:ValueKeyit[5, 2][5, 2][4, 1][1, 1]wasgreatterribleThere is no console output for Part A.What is a word? When designing a program like this, you need to make sure that you and theprogram's end users agree on what counts as a unique word. For this assignment:• Ignore capitalization: &#34;And&#34; and &#34;and&#34; should be counted as the same word.Do not worry about punctuation, symbols, or numbers within the review text - you do notneed to remove these. Just put everything you find into your dictionary. Your dictionarywill have entries that are just symbols (ex. &#34;.&#34; or &#34;,&#34;) and also entries that are numbers.• Make sure strip out all whitespace from each word. For example, you should not havewords in your dictionary that contain a space, tab character (&#34;	&#34;), or newline (“
&#34;).Part B: Creating Word ScoresAfter your dictionary has been created and filled in Part A, ask the user to enter a word in theconsole.If that word exists in the dictionary, print out the number of times that word occurred in themovie review file and the average rating for that word. The average rating is the total scoredivided by the number of times that word occurred in the movie review file.Imagine our movie review file contains the same two reviews from Part A.Here are 3 example sessions (user input in blue):Enter a word: Great'great' appears 1 time(s) and has an average rating of 4.End of Processing.Enter a word: it'it' appears 2 time(s) and has an average rating of 2.5.End of Processing.Enter a word: haberdashery'haberdashery' does not appear in any movie reviews.End of Processing.4

Accepted Answer

logic:- 
Set sum=0
iterate from i=0 to i<length of array
  sum=sum+arr[i]
end loop
display length…