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Social Network Analysis: #BlackLivesMatter Distribution at Actor Level and System Level

Jurnal Komunikasi Ikatan Sarjana Komunikasi Indonesia (JKISKI) · Vol. 6 No. 2 (2021) · pp. 275–283

DOI
10.25008/jkiski.v6i2.577
ISSN
2503-0795, 2548-8740
Published
2021-12-09
Publisher
Jurnal Komuniksi ISKI
License
creativecommons.org/licenses/by-sa/4.0

Abstract

#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.

Collaboration network of the authors

9 authors · 20 co-authorship links

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  • Gunadarma University
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Noviawan Rasyid OhorellaGunadarma University2
Atit PertiwiGunadarma University2
Suryarini WidodoGunadarma University2
Rio Setia MonataGunadarma University2
Yusuf MaulanaGunadarma University2
Dwi HaryantiGunadarma University1
Ainun Rahma YusufinaGunadarma University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2503-0795/works, first harvested 29 Okt 2026, last seen 29 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Social Network Analysis: #BlackLivesMatter Distribution at Actor Level and System Level</dc:title><dc:creator>Prihantoro, Edy</dc:creator><dc:creator>Ramadhani, Rizky Wulan</dc:creator><dc:description>&lt;jats:p&gt;#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.&lt;/jats:p&gt;</dc:description><dc:publisher>Jurnal Komuniksi ISKI</dc:publisher><dc:date>2021-12-09</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.25008/jkiski.v6i2.577</dc:identifier><dc:identifier>10.25008/jkiski.v6i2.577</dc:identifier><dc:source>Jurnal Komunikasi Ikatan Sarjana Komunikasi Indonesia; Vol 6 No 2 (2021); 275-283</dc:source><dc:source>2503-0795</dc:source><dc:source>2548-8740</dc:source><dc:relation>http://www.jurnal-iski.or.id/index.php/jkiski/article/viewFile/577/pdf</dc:relation><dc:rights>https://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>