Standardize scores and remove the reviews with no rating. Replace nominal scores

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

Web page mining

Assignment Specification

Description: Choose a popular movie you like and find the id of this movie at rottentomatoes.com

• https://www.rottentomatoes.com/m/hamilton_2020/reviews

• Movie id = “hamilton_2020”

• Hamilton has 10 pages of reviews. You need to collect reviews from all the pages

• Create a list of lists [review, score], where “review” is the review text content and “score” is the rate given for each review. This score can be a nominal grade, fraction or can be missing – see picture

• Rank reviews by score

Procedure:

• Import the needed libraries

• Define the target URL and open it

• Load the page into your “soup”/beautifulsoup

• Identify the total number of pages 

• Loop through each page, creating a new soup every time

• Collect review and respective score

• Generate a list of lists for the reviews

• Standardize scores and remove the reviews with no rating. Replace nominal scores (where they appear) with numerical values: A+':5, 'A':4.8, 'A-': 4.6, 'B+':4.45, 'B':4.3, 'B-':4.1, 'C+':3.95, 'C':3.8, 'C-':3.6, 'D+':3.45, 'D':3.3, 'D-':3.1. Normalize the numerical values in a scale 1 to 5.

• Document your findings. This would include:

• top 5 and bottom 5 reviews lists 

• a word cloud for each of them (top and bottom)

• Be sure to use only the text part of the reviews list of lists and to clean stop words using the stopword_en.txt file.

Attachments:

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