A New Greedy Algorithm For Influence Maximization On Signed Social Networks

Year 2019, Volume: 5 Issue: 3, 250 - 257, 30.12.2019

Aybike Şimşek

https://doi.org/10.30855/gmbd.2019.03.06

Abstract

The social
influence is one of the major phenomenons that shapes people's decisions. In
this respect, Influence Maximization (IM) problem is one of the most attractive
research topics in the social network analysis because its practical benefits
in viral marketing, public opinions shaping etc. The IM problem aims to
maximize the spread of an influence (e.g. an opinion, an advertisement) in a
social network by using a small number of the most effective individuals, whom
is called influencers. Detecting the
influencers is the NP-Hard combinatorial optimization problem in most cases. Therefore,
many algorithms have been and are being developed for the IM problem. However,
the algorithms have not yet achieved to the desired solution quality and speed.
In this study, we focused on the signed IM problem that is considers both
positive and negative influence between the individuals. For this purpose, we
developed a greedy algorithm called the Elitist Greedy Algorithm (EGA) for
detecting  influencers set. We compared the EGA’s
performance on 2 public datasets with random seed selection, out degree
heuristic, and one state-of-the-art greedy algorithm. The EGA outperforms the
competitors in terms of the achieved total influence.

Keywords

Influence maximization, online social networks, information diffusion, greedy algorithm

İşaretli Sosyal Ağlarda Etki Maksimizasyonu İçin Yeni Bir Aç Gözlü Algoritma

Abstract

Sosyal etki insanların görüşlerini şekillendiren
büyük olgulardan biridir. Bu bakımdan, Etki Maksimizasyonu (EM) problemi viral
pazarlama, kamuoyu şekillendirme gibi pratik faydaları olduğu için sosyal ağ
analizinde en fazla ilgili çeken araştırma alanlarından biridir. EM probleminin
amacı bir sosyal ağ üzerindeki etkili
kişi olarak adlandırılan az sayıdaki kişiyi kullanarak bir etkinin (bir
fikir veya reklam) ağ üzerindeki yayılımını maksimize etmektir. Etkili
kişilerin tespiti birçok durumda NP-Hard bir kombinasyonal optimizasyon
problemidir. Bundan dolayı, EM problemi için birçok algoritma geliştirilmiştir
ve geliştirilmeye devam etmektedir. Ne var ki, geliştirilen algoritmalar henüz
çözüm kalitesi ve hız açısından istenen seviyede değildirler. Bu çalışmada,
bireyler arasındaki olumlu ve olumsuz ilişkileri göz önünde bulunduran işaretli
EM problemine odaklanılmıştır. Bu amaçla, en iyi  adet
etkili kişiyi tespit etmek için Elitist Aç Gözlü Algoritma (EGA) olarak
adlandırılan bir aç gözlü algoritma geliştirmiştir. EGA’nın performansı 2 adet
açık veriseti üzerinde rasgele seçim, çıkış derecesi merkeziliği, ve bir güncel
algoritma ile kıyaslanmıştır. EGA çözüm kalitesi açısından rakiplerine göre
daha iyi sonuçlar vermiştir.

Keywords

Etki maksimizasyonu, online sosyal ağlar, bilgi yayılımı, aç gözlü algoritma

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