Abstract: In this paper, we present snowball-chain (SbChain+) approach, which is an improved version of SbChain community detection method in terms of precision with which communities are identified in a social graph. It exploits the topology of a social graph in terms of the connections of a node, i.e., its degree centrality, betweenness centrality and the number of links within its neighborhood defined by the local clustering coefficient. Two different functions have been used to identify neighbors for a given node. Hence, two approaches have been discussed with their pros and cons. In general, SbChain+ takes a social graph as an input and aims to identify communities around the core nodes in the underlying network. The core nodes are expected to have a high degree and have densely connected neighbors and guides in identifying cliques from the graph. The proposed approach takes its inspiration from snowball sampling technique and keeps merging the nodes with their neighboring nodes based on certain criteria to form snowballs. One of the functions discussed (SbChain+(i)) uses a hyperparameter, λ for merging snowballs which further leads to the formation of communities. This hyperparameter also helps in achieving the desired level of coarseness in the communities, and it can be adjusted to fine tune the identified communities. While the second function (SbChain+(ii)) uses an average out degree function to merge snowballs. The modularity values are calculated at each level of the dendrogram formed by combining nodes and snowballs to decide an appropriate cut for community determination. SbChain+ is empirically evaluated using these two different functions over both real-world and LFR-benchmark datasets and results are evaluated on modularity and normalized mutual information. The aim of this study is to improve upon the previously discussed technique (SbChain) and to study the use of hyperparameter, i.e., the performance of a technique with or without the hyperparameter.

Jayati Gulati and Muhammad Abulaish, “SbChain+: An Enhanced Snowball-Chain Approach for Detecting Communities in Social Graphs” International Journal of Advanced Computer Science and Applications(IJACSA), 14(6), 2023. http://dx.doi.org/10.14569/IJACSA.2023.01406121

@article{Gulati2023,
title = {SbChain+: An Enhanced Snowball-Chain Approach for Detecting Communities in Social Graphs},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.01406121},
url = {http://dx.doi.org/10.14569/IJACSA.2023.01406121},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {6},
author = {Jayati Gulati and Muhammad Abulaish}
}