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Social Network Analysis: #BlackLivesMatter Distribution at Actor Level and System Level
Author(s) -
Edy Prihantoro,
Rizky Wulan Ramadhani
Publication year - 2021
Publication title -
jurnal komunikasi ikatan sarjana komunikasi indonesia
Language(s) - English
Resource type - Journals
eISSN - 2548-8740
pISSN - 2503-0795
DOI - 10.25008/jkiski.v6i2.577
Subject(s) - betweenness centrality , centrality , closeness , social network analysis , reciprocity (cultural anthropology) , value (mathematics) , sociology , social media , political science , computer science , social science , statistics , law , mathematical analysis , mathematics , machine learning
#BlackLivesMatter accompanies several cases of discrimination against the black community. The hashtag was spread by actors who have great influences on Twitter users. The actors create communication network which connected to each other to form opinions about the Black Lives Matter movement. Researchers conducted a study to determine the distribution of #BlackLivesMatter at the actor level for the period 20-27 April 2021 in Twitter. The study used quantitative methods and a positivistic paradigm with a Social Network Analysis (SNA) approach. The results show that the actor with the highest degree of centrality is @jeanmessiha with 238 interactions, the actor with the highest betweenness centrality is @helloagain0611 with a value of 0.000049, the actor with the highest eigenvector centrality is @jeanmessiha with a value of 1 and there are 1,416 actors who have closeness centrality. # BlackLivesMatter has a low diameter value so that it spreads quickly but not too widely, not much reciprocity occurs, not concentrated in one dominant cluster but spread widely in several clusters. The actors play a role in spreading diverse opinions regarding Black Lives Matter, thus creating free discussion in several clusters on Twitter. Opinion widely spread on Twitter creates public opinion regarding the Black Lives Matter movement.

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