Friends Recommendation in Dynamic Social Networks Using Breadth-First Search Algorithm
Session
Computer Science and Communication Engineering
Description
Social networks are constantly evolving, and recommending new con- nections is essential for improving user engagement. This paper proposes a friend recommendation system using the Breadth-First Search (BFS) algorithm on dy- namic graphs, offering a simple, scalable, and efficient solution. The network is modeled as an undirected graph, where users are vertices and friendships are edges. BFS explores the graph level by level, identifying potential friends through mutual connections while excluding existing friends. An adjacency list representation ensures memory efficiency and supports real-time updates. Can- didate friends are ranked by the number of shared mutual connections, with higher counts indicating stronger recommendations. The system was imple- mented with both console-based and graphical user interfaces, allowing users to add members, manage friendships, and generate recommendations. Results show that BFS provides fast response times and generates meaningful suggestions in dynamic social networks, making it an effective and practical algorithm for real- time friend recommendation.
Keywords:
Friend Recommendation, BFS, Social Networks, Dynamic Graphs, Scalability
Proceedings Editor
Edmond Hajrizi
ISBN
978-9951-982-41-2
Location
UBT Lipjan, Kosovo
Start Date
25-10-2025 9:00 AM
End Date
26-10-2025 6:00 PM
DOI
10.33107/ubt-ic.2025.110
Recommended Citation
Pira, Rigon; Domi, Jeta; Qehaja, Besnik; and Hajrizi, Edmond, "Friends Recommendation in Dynamic Social Networks Using Breadth-First Search Algorithm" (2025). UBT International Conference. 42.
https://knowledgecenter.ubt-uni.net/conference/2025UBTIC/CS/42
Friends Recommendation in Dynamic Social Networks Using Breadth-First Search Algorithm
UBT Lipjan, Kosovo
Social networks are constantly evolving, and recommending new con- nections is essential for improving user engagement. This paper proposes a friend recommendation system using the Breadth-First Search (BFS) algorithm on dy- namic graphs, offering a simple, scalable, and efficient solution. The network is modeled as an undirected graph, where users are vertices and friendships are edges. BFS explores the graph level by level, identifying potential friends through mutual connections while excluding existing friends. An adjacency list representation ensures memory efficiency and supports real-time updates. Can- didate friends are ranked by the number of shared mutual connections, with higher counts indicating stronger recommendations. The system was imple- mented with both console-based and graphical user interfaces, allowing users to add members, manage friendships, and generate recommendations. Results show that BFS provides fast response times and generates meaningful suggestions in dynamic social networks, making it an effective and practical algorithm for real- time friend recommendation.