Social Network Simulator

A social media simulation implemented in C, combining user management, friendship graphs, post/repost systems, and user feed generation.
The program integrates graph traversal, BFS algorithms, and data structures such as linked lists and trees to emulate core social platform features.

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Overview

The project models a simplified social network divided into three main components:

1. Users and Friends – manages connections between accounts
2. Posts and Reposts – handles content creation and interaction
3. Social Media Integration – combines both systems for feed and profile simulation

Each command follows a consistent structure:

• Parse input arguments
• Execute the corresponding operation
• Print results or success messages

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Features

1. Users and Friends

Implements the social graph using an adjacency matrix.
Supports:

• Adding or removing friends
• Computing shortest distance between two users (via BFS)
• Suggesting friends of friends
• Finding common friends
• Counting friends per user
• Determining the most popular account

Key functions:

• add_friend(), remove_friend()
• distance_friend() — uses BFS for shortest path
• suggestions_friend() — finds second-degree connections
• common_people() — intersection of friend lists
• friends() — counts user connections
• influencer() — finds the account with most friends

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2. Posts and Reposts

Implements user-generated content using:

• A doubly linked list for posts
• A tree structure for reposts

Supports:

• Creating and deleting posts
• Reposting existing content
• Liking and unliking posts
• Computing ratios between posts and reposts
• Viewing repost trees and like counts

Key algorithms:

• Tree traversal for reposts
• Parent tracking for common repost origins
• Array-based like tracking per post

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3. Social Media Integration

Combines both modules into a unified simulation of:

• User feed — retrieves most recent posts by user and friends
• Profile view — shows a user’s posts in chronological order
• Friends that reposted — lists a user’s friends who reposted a given post
• Clique detection — finds maximal cliques using the Bron–Kerbosch algorithm

The recursive Bron–Kerbosch algorithm computes all maximal friend groups, using sets:

• R — current clique
• P — potential candidates
• X — excluded vertices

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Example Commands

add_friend user1 user2
remove_friend user3 user4
create_post user1 "Hello world!"
repost user2 3
like user3 3
feed user1 5
view_profile user2
friends_that_reposted user1 3
bk

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Learning Outcomes

• Applied advanced data structures (graphs, lists, trees)
• Implemented BFS and Bron–Kerbosch graph algorithms
• Managed dynamic memory safely in complex interlinked structures
• Simulated realistic interactions between users and posts in C