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A Social Network Analysis of the #AllEyesOnRafah on X Social Media

Bibliographic Data

ID21987539
AuthorsWahyuddin Wahyuddin (0000-0001-7092-7184, Hasanuddin University), Reynaldi Reynaldi (Hasanuddin University), Rustono Farady Marta (0000-0002-2282-4081, University of Bunda Mulia), Engliana Engliana (0000-0001-8144-5068, Atma Jaya Catholic University of Indonesia), Iskandar Iskandar (0000-0001-6336-1741, Institut Agama Islam Negeri Bengkulu)
Year2024
Volume16
Issue1
Pages20-39
Publication date2024-10-28
Open AccessYes
TypeARTICLE
VenueUltimacomm (JOURNAL)
Journal identifiersISSN: 2085-4609 • E-ISSN: 2656-0208
PublisherUniversitas Multimedia Nusantara (PUBLISHER)
DOI10.31937/ultimacomm.v16i1.3722
OpenAlexW4410259175
LanguageEN

The slogan ‘All Eyes on Rafah' went viral and became the talk of netizens on social media. The viral hashtag #AllEyesOnRafah on X social media was used to voice solidarity and concern for the humanitarian tragedy that befell the people of Rafah due to the Israeli army's attack. This study, conducted using the rigorous Social Network Analysis (SNA) method and incorporating the computer-mediated communication (CMC) theory and the Homophily theory, seeks to identify influential actors and analyze the communication network of the #AllEyesOnRafah on X social media. The primary data is the posts on social media X with the hashtag #AllEyesOnRafah dated from May 26th to July 4th, 2024. The data collection, processing, and analysis uses the web-based applications Netlytic.org and Gephi software. The SNA analysis reveals 305 nodes and 382 edges centered on several actors. The proximity between actors is 3, showing that the distance between actors is close. Therefore, the interactions are easy to occur. It was also found that the interactions between actors were few and considered uneven; this fact signifies one-way interactions. Such interaction is centered on 10 nodes with the most dominant of which is the @realmarcel1 account. In addition to that, the two most influential actors, @realmarcel1 and @Ta4leaHayam1, consistently scored highest in centrality on the basis of the analysis of degree centrality, closeness centrality, betweenness centrality, and eigenvector centrality. The communication network encouraged X users to support Palestine and informed others

Social media · Social network analysis · Sociology · World Wide Web · Computer Science · Misinformation and Its Impacts · Public Relations and Crisis Communication · Social Media and Politics

Highly citedNo

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