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Xing, Y. (2014) A Node Influence Based Label Propagation Algorithm for Community Detection in Networks. The Scientific World Journal, 2014, Article ID: 627581.

has been cited by the following article:

  • TITLE: The Effects of Centrality Ordering in Label Propagation for Community Detection

    AUTHORS: Brian Dickinson, Wei Hu

    KEYWORDS: Community Detection, Label Propagation, Centrality, Overlapping Community Detection

    JOURNAL NAME: Social Networking, Vol.4 No.4, October 9, 2015

    ABSTRACT: In many cases randomness in community detection algorithms has been avoided due to issues with stability. Indeed replacing random ordering with centrality rankings has improved the performance of some techniques such as Label Propagation Algorithms. This study evaluates the effects of such orderings on the Speaker-listener Label Propagation Algorithm or SLPA, a modification of LPA which has already been stabilized through alternate means. This study demonstrates that in cases where stability has been achieved without eliminating randomness, the result of removing random ordering is over fitting and bias. The results of testing seven various measures of centrality in conjunction with SLPA across five social network graphs indicate that while certain measures outperform random orderings on certain graphs, random orderings have the highest overall accuracy. This is particularly true when strict orderings are used in each run. These results indicate that the more evenly distributed solution space which results from complete random ordering is more valuable than the more targeted search that results from centrality orderings.