Sentiment Classification of a Review | Dataford Interview Questions

Given lists of positive and negative words and a review, determine if the review is positive, negative or neutral.

Asked in the technical phone stage.

Implement classify_review(positive_words, negative_words, review). Treat matching as case-insensitive and whole-word based. Ignore punctuation. Return "positive" when positive matches outnumber negative matches, "negative" when negative matches outnumber positive matches, and "neutral" when the counts are equal. Repeated words count repeatedly. The positive and negative lists are disjoint.

Constraints

1 <= len(positive_words) + len(negative_words) <= 10^4
1 <= len(review) <= 10^5
Each sentiment word contains letters and may contain an apostrophe
The positive and negative word lists are disjoint
Matching is case-insensitive and based on complete words

Function Signature

def classify_review(positive_words, negative_words, review):

Your question is Sentiment Classification of a Review. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Problem

Given lists of positive and negative words and a review, determine if the review is positive, negative or neutral.

Asked in the technical phone stage.

Constraints

1 <= len(positive_words) + len(negative_words) <= 10^4
1 <= len(review) <= 10^5
Each sentiment word contains letters and may contain an apostrophe
The positive and negative word lists are disjoint
Matching is case-insensitive and based on complete words

Function Signature

def classify_review(positive_words, negative_words, review):

Your question is Sentiment Classification of a Review. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.