Imagine you have a Twitter-style social network.
Each post can have multiple tags.
Your task:
Return the top X most frequent tags used by your friends and your friends-of-friends.
In other words, starting from a given user:
- Look at all friends (1-hop)
- Look at all friends of friends (2-hop)
- Aggregate all tags from all posts of those users
- Return the Top X frequent tags
Example (conceptual):
User → friends: A, B
A’s tags: ["sports", "fun"]
B’s tags: ["news", "sports"]
A’s friends: C
C’s tags: ["travel", "sports"]
If X = 2, output:
["sports", "fun"] # For example (depends on actual counts)
Use BFS up to depth 2 to collect friends and friends-of-friends.
Count tag frequencies with a hash map, then return the top X using a min-heap or sorting.
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