Part $3$: Should I watch it$?[25$ marks$]$

Note: This is just a simplified method of doing textual analysis, but it is a good exposure to see how we

could use code to help us determine certain sentiments$.$

Even though the movie has been released quite a while ago, your younger cousin has been pestering you

to watch Frozen II with her. You do not really enjoy watching movies but maybe if the movie reviews are

good enough...

In this part, you will be given a few movie reviews to analyse. A file, sent$\_$scores.txt$,$ has been loaded in for

you where each word is assigned a certain score $(>0$ means it's a positive word while $<mn\; id="EditorElement\_3088197">0</mn>$ means it's a

negative word$).$

Your task is to write a function score$($file$)$ that takes in the file path of a movie review and output the

corresponding sentiment score and most impactful word within the review.

Input:

file $-$ This is the $.$txt file that you want to analyse. Ensure that the txt file is in the same folder as

your python file

Output:

A $2-$element tuple. The first element is the sum of the sentiment scores, rounded to $2$ decimal

places. The second element is the word that has the highest impact within the article.

To illustrate how these $2$ elements are calculated, refer to the example below:

In the template, we have read in the file sent$\_$scores.txt as a variable word$\_$scores. This contains a list of

lists in a format like this $[[\text{'}$vile$\text{'},\text{'}-3\mathrm{.}18\text{'}],[\text{'}$tragic$\text{'},\text{'}-3\mathrm{.}15\text{'}],[\text{'}$ugly$\text{'},\text{'}-3\mathrm{.}10\text{'}],[\text{'}$pastel$\text{'},\text{'}0\mathrm{.}47\text{'}]].$ This means

"vile" is associated with a $-3\mathrm{.}18$ score, "tragic" is $-3\mathrm{.}10,$ "pastel" is $0\mathrm{.}47,$ etc.