Finding The Most Important Actor in Online Crowd by Social Network Analysis

International Seminar on Mathematics, Science, and Computer Science Education 2016

数学;自然科学;计算机科学

Yuliana, I.^1 ; Santosa, P.I.^2 ; Setiawan, N.A.^2 ; Sukirman^1

Department of Informatics Engineering Education, Universitas Muhammadiyah Surakarta (UMS), Jl. Ahmad Yani No. 1, Pabelan, Surakarta

57162, Indonesia^1

Departement of Electrical Engineering, Universitas Gadjah Mada, Jl. Grafika No. 2, Sleman, Yogyakarta

55281, Indonesia^2

关键词: Bushfires;    Critical issues;    Greenpeace;    Human behaviours;    On-line communities;    Social media;    Social participation;    Sociometrics;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/812/1/012095/pdf
DOI  :  10.1088/1742-6596/812/1/012095

来源: IOP

【 摘 要 】

Billion of people create trillions of connections through social media every single day. The increasing use of social media has led to dramatic changes in the of way science, government, healthcare, entertainment and enterprise operate. Large-scale participation in Technology-Mediated Social Participation (TMSP) system has opened up incredible new opportunities to deploy online crowd. This descriptive-correlational research used social network analysis (SNA) on data gathered from Fanpage Facebook of Greenpeace Indonesia related to important critical issues, the bushfires in 2015. SNA identifies relations on each member by sociometrics parameter such as three centrality (degree, closeness and betweenesse) for measuring and finding the most important actor in the online community. This paper use Fruchterman Rein-gold algorithm to visualize the online community in a graph, while Clauset-Newman-Moore is a technique to identify groups in community. As the result found 3735 vertices related to actors, 6927 edges as relation, 14 main actors in size order and 22 groups in Greenpeace Indonesia online community. This research contributes to organize some information for Greenpeace Indonesia managing their potency in online community to identify human behaviour.