Implement Review Content Moderation

Problem Statement

You are building a moderation service for a product review platform. Your task is to process incoming review text and determine if it should be flagged based on a set of prohibited words.

Requirements

1. Moderation Check: A review is considered 'flagged' if it contains one or more words from a dynamic list of prohibited_words.
2. Stateful Tracking: You must track the total number of flagged reviews submitted by each user_id.
3. Persistence/Update: The list of prohibited_words can be updated at runtime. The system must use the current list for every incoming check.

Implement a class ReviewModerator with the following methods:

• __init__(self, prohibited_words): Initialize the moderator with a set of prohibited words.
• process_review(self, user_id, review_text): Returns True if the review contains any prohibited words, False otherwise. If flagged, increment the user's violation count.
• get_violation_count(self, user_id): Return the total number of flagged reviews for a given user.
• update_prohibited_words(self, new_words): Update the master list of prohibited words.

Constraints

• review_text can contain punctuation; treat words as case-insensitive sequences separated by whitespace.
• user_id is a string.
• Efficiency: The process_review method should be optimized for high-frequency calls, as review volume is high.

Example

moderator = ReviewModerator({"spam", "bot"})
moderator.process_review("user1", "This is a great product") # Returns False
moderator.process_review("user1", "This is spam")           # Returns True
moderator.get_violation_count("user1")                      # Returns 1

Edge Cases

• Empty review_text.
• Overlapping prohibited words (e.g., if 'spam' and 'spammy' are both prohibited).
• Case-sensitivity: 'Spam' should be treated the same as 'spam'.