Analisis Penyebaran Informasi Vaksin Covid-19 Pada Twitter Menggunakan Kolaborasi SNA dan Sentiment Analysis
DOI:
https://doi.org/10.30865/mib.v6i2.3955Keywords:
Social Network Analysis, Sentiment Analysis, Support Vector Machine, Twitter, Covid-19 VaccineAbstract
The use of the Covid-19 vaccine as an effort to overcome and protect the Indonesian people from the Covid-19 pandemic has been widely discussed on Twitter social media. The existence of the Covid-19 vaccine in Indonesia has drawn various opinions because of the large amount of information shared by Twitter users regarding the Covid-19 vaccine. This study uses the collaboration of social network (SNA) and sentiment analysis. In this study, SNA collaborated with sentiment analysis to classify positive and negative sentiments in news spread by influential actors based on groups formed in the SNA network. SNA research shows there are 6 influential actors based on the group formed in the network. The actors with the highest popularity are @KemenkesRI with a degree of centrality reaching 194, while actors with the lowest degree of centrality are @rudeski83. In addition, actors with the highest centrality betweenness are @KemenkesRI because it plays an important role in disseminating information about the Covid-19 vaccine on social media twitter. SVM classification test results showed @KemenkesRI actor with an accuracy rate of 97% and @Vaksin_Update with an accuracy rate of 90% are actors with a positive sentiment percentage of 95%, while actors @rudeski83with an accuracy rate of 98% is an actor with a negative sentiment percentage of 80%. Based on the above, it can be seen that the SNA collaboration and sentiment analysis carried out showed that 5 out of 6 actors who were influential actors based on the group formed in the network.
References
H. Basri and Syafrizal, “Peran Media Sosial Twitter Dalam Interaksi Sosial Pelajar Sekolah Menengah Pertama Di Kota Pekanbaru,†JOM FISIP Vol. 4 No. 2 – Oktober 2017 Page 1, 4(1), 1–13., 2017, doi://media.neliti.com/media/publications/183768-ID-partisipasi-masyarakat-dalam-pelaksanaan.pdf.
A. Srivastava, S.Vijendra, and D.G. Singh, “Sentiment analysis of twitter data: A hybrid approach,†International Journal of Healthcare Information Systems and Informatics, 14(2), 1–16, 2019, doi://doi.org/10.4018/IJHISI.2019040101.
WHO, “COVAX Statement on New Variants of SARS-Cov-2 on 8 February 2021,†2020. Diakses 19 Februari 2021, Tersedia: https://www.who.int/news/item/08-02-2021-covax-statement-on-new-variants-of-sars-cov-2
F.B. Hasan, “Panduan Ringkas Covid-19 dan Vaksin,†2021.
S. A. Nugroho and I. N. Hidayat, “Efektivitas Dan Keamanan Vaksin Covid-19,†Jurnal Keperawatan, 9, 47, 2021, doi://ejournal.unuja.ac.id/index.php/jkp/article/download/2767/1002.
E. Lazega, S. Wasserman, and K. Faust, “Social Network Analysis: Methods and Applications,†Revue Française de Sociologie, 36(4), 781, 1995.
A. Iriani, “Using Social Network Analysis to Analyze Collaboration in Batik Smes,†Journal of Knowledge Management, Economics and Information Technology, 3(6), 1–18, 2013, doi: ://www.scientificpapers.org/download/287/.
B. Liu, “Sentiment Analysis: Mining Opinions, Sentiments, and Emotions,†Cambridge University Press, 2015.
J. A. K. Suykens, M. Signoretto, and A. Argryou, “Regularization, Optimization, Kernels and Support Vector Machine,†CRC Press, 2014.
B. S. D and D. Gore, “Sentiment Analysis On Twitter Data Using Support Vector Machine,†International Journal of Computer Science Trends and Technology (IJCST) –, 4(3), 831–837, 2016, doi://www.ijcstjournal.org/volume-4/issue-3/IJCST-V4I3P61.pdf.
J. Ipmawati, Kusrini, and E. T. Luthfi, “Komparasi Teknik Klasifikasi Teks Mining Pada Analisis Sentimen,†Indonesian Journal on Networking and Security, 6(1), 28–36, 2017, doi://dx.doi.org/10.55181/ijns.v6i1.1444.
M. N. Habibi and Sunjana, “Analysis of Indonesia Politics Polarization before 2019 President Election Using Sentiment Analysis and Social Network Analysis,†International Journal of Modern Education and Computer Science, 11(11), 22–30, 2019, doi://doi.org/10.5815/ijmecs.2019.11.04.
L. Tomasoa, A. Iriani and I. Sembiring, “Ekstraksi Knowledge tentang Penyebaran #RATNAMILIKSIAPA pada Jejaring Sosial (Twitter) menggunakan Social Network Analysis (SNA),†Jurnal Teknologi Informasi Dan Ilmu Komputer, 6(6), 677, 2019, doi://doi.org/10.25126/jtiik.2019661710.
B. Laurensz and E. Sediyono, “Analisis Sentimen Masyarakat terhadap Tindakan Vaksinasi dalam Upaya Mengatasi Pandemi Covid-19,†Jurnal Nasional Teknik Elektro dan Teknologi Informasi 10(2), 118–123, 2021, doi://doi.org/10.22146/jnteti.v10i2.1421.
C. Casanueva, A. Gallego, and M. R. G. Sánchez, “Social network analysis in tourism,†Current Issues in Tourism, 19(12), 1190–1209, 2016, doi://doi.org/10.1080/13683500.2014.990422.
R. Alhajj and J. Rokne, “Encyclopedia of Social Network Analysis and Mining, Springer Science+Business Media LLC, part of Springer Nature, 2018.
S. Khairunnisa, Adiwijaya, and S. Al. Faraby, “Pengaruh Text Preprocessing terhadap Analisis Sentimen Komentar Masyarakat pada Media Sosial Twitter (Studi Kasus Pandemi COVID-19),â€Jurnal Media Informatika Budidarma, 5(2), 406, 2021, doi://doi.org/10.30865/mib.v5i2.2835.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
