How do you solve Find Emotionally Consistent Users on LeetCode?

Find Emotionally Consistent Users (LeetCode #3808) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(n) space complexity. Key insight: Users must react to at least 5 different contents.

What is the time complexity of Find Emotionally Consistent Users?

The optimal solution for Find Emotionally Consistent Users runs in O(n) time and uses O(n) space. This complexity is linear due to processing each reaction once and using hash maps for counting.

What is the brute force solution for Find Emotionally Consistent Users?

The brute force approach for Find Emotionally Consistent Users is Brute Force, with O(n²) time complexity and O(1) space complexity. Count reactions for each user and check consistency by comparing each reaction type. This method is straightforward but inefficient. The optimal Optimal Solution approach improves this to O(n).

What are the interview tips for Find Emotionally Consistent Users?

Clarify the requirements before coding. Discuss edge cases like users with no reactions. Explain your thought process while coding.

What are common mistakes when solving Find Emotionally Consistent Users?

Ignoring users with fewer than 5 reactions. Not rounding the reaction ratio correctly.

#3808

Find Emotionally Consistent Users

Medium

Hash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(n)

💡

Intuition

Time O(n)Space O(n)

Use a single pass to count reactions and determine consistency, leveraging hash maps for efficient counting.

⚙️

Algorithm

3 steps

1Step 1: Count each user's reactions and the number of distinct content items.
2Step 2: Calculate the maximum reaction count and check if it meets the 60% threshold.
3Step 3: Return users who meet the criteria, sorted by reaction ratio and user ID.

solution.py1 lines

1SELECT user_id, ROUND(MAX(count) / total_reactions * 100, 2) AS reaction_ratio FROM (SELECT user_id, reaction, COUNT(*) AS count, COUNT(DISTINCT content_id) AS total_reactions FROM reactions GROUP BY user_id, reaction) AS user_reactions WHERE total_reactions >= 5 GROUP BY user_id HAVING MAX(count) / total_reactions >= 0.6 ORDER BY reaction_ratio DESC, user_id ASC;

ℹ

Complexity note: This complexity is linear due to processing each reaction once and using hash maps for counting.

1Users must react to at least 5 different contents.
2Consistency is defined by the majority reaction type.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.