Social
network analysis (SNA) is a very popular research area that helps to
analyze social structures through graph theory. Objects in social structures
are represented by nodes and are modeled according to the relations (edges)
they establish with each other. The determination of community structures on
social networks is very important in terms of computer science. In this study,
the Invasive Weed Optimization (IWO) algorithm is proposed for the
detection of meaningful communities from social networks. This algorithm is
proposed for the first time in community detection (CD). In addition,
since the algorithm works in continuous space, it is made suitable for solving
the CD problems by being discretized. The experimental studies are
conducted on human-social networks such as Dutch College, Highland Tribes, Jazz
Musicians and Physicians. The results obtained from experimental results are
compared and analyzed in detail with the results of the Bat Algorithm and Gravitational
Search Algorithm. The comparative results indicate that IWO algorithm is an alternative technique in solving CD
problem in terms of solution quality.
Community detection discretization invasive weed optimization social networks SNA
Bölüm | Articles |
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Yazarlar | |
Yayımlanma Tarihi | 8 Eylül 2017 |
Yayımlandığı Sayı | Yıl 2017 Cilt: 7 |