A Novel Hybrid Approach Combining Beam Search and DeepWalk for Community Detection in Social Networks

Aymene Berriche, Marwa Naïr, Kamel Yamani, Mehdi Adjal, Sarra Bendaho, Nidhal Chenni, Fatima Tayeb, Fatima Tayeb, Malika Bessedik, Malika Bessedik

2023

Abstract

In the era of rapidly expanding social networks, community detection within social graphs plays a pivotal role in various applications such as targeted marketing, content recommendations, and understanding social dynamics. Community detection problem consists of finding a strategy for detecting cohesive groups, based on shared interests, choices, and preferences, given a social network where nodes represent users and edges represent interactions between them. In this work, we propose a hybrid method for the community detection problem that encompasses both traditional tree search algorithms and deep learning techniques. We begin by introducing a beam-search algorithm with a modularity-based agglomeration function as a foundation. To enhance its performance, we further hybridize this approach by incorporating DeepWalk embeddings into the process and leveraging a novel similarity metric for community structure assessment. Experimentation on both synthetic and real-world networks demonstrates the effectiveness of our method, particularly excelling in small to medium-sized networks, outperforming widely adopted methods.

Paper Citation

in Harvard Style

Berriche A., Naïr M., Yamani K., Adjal M., Bendaho S., Chenni N., Tayeb F. and Bessedik M. (2023). A Novel Hybrid Approach Combining Beam Search and DeepWalk for Community Detection in Social Networks. In Proceedings of the 19th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST; ISBN 978-989-758-672-9, SciTePress, pages 454-463. DOI: 10.5220/0012231500003584

in Bibtex Style

@conference{webist23,
author={Aymene Berriche and Marwa Naïr and Kamel Yamani and Mehdi Adjal and Sarra Bendaho and Nidhal Chenni and Fatima Tayeb and Malika Bessedik},
title={A Novel Hybrid Approach Combining Beam Search and DeepWalk for Community Detection in Social Networks},
booktitle={Proceedings of the 19th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST},
year={2023},
pages={454-463},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012231500003584},
isbn={978-989-758-672-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST
TI - A Novel Hybrid Approach Combining Beam Search and DeepWalk for Community Detection in Social Networks
SN - 978-989-758-672-9
AU - Berriche A.
AU - Naïr M.
AU - Yamani K.
AU - Adjal M.
AU - Bendaho S.
AU - Chenni N.
AU - Tayeb F.
AU - Bessedik M.
PY - 2023
SP - 454
EP - 463
DO - 10.5220/0012231500003584
PB - SciTePress