Analysis of Selective Exposure Cluster in the Covid-19 Vaccine Information Network on Twitter
- DOI
- 10.2991/978-2-494069-07-7_51How to use a DOI?
- Keywords
- cluster; selective exposure; information network; covid-19 vaccine; twitter
- Abstract
The purpose of this study was to identify clusters formed in the Twitter network related to the topics of the Covid-19 vaccine. This study uses a quantitative approach with social network analysis with selective exposure cluster method. The population of this study is the use of the Twitter social network with the keyword “covid-19 vaccine” as a cluster sample. Data is collected using the NodeXL application. The data were analyzed by grouping based on the Clauset-Newman-Moore algorithm cluster by calculating the entire network of users, the level of hubs in the cluster, grouping in the network, finding the highest twitter network. The results showed that official government accounts, political figures, and mass media simultaneously appeared in all data sets so that they formed a cluster that consistently supported the success of the national vaccination program.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Fadlih Awwal Hasanuddin AU - Muh. Akbar AU - Muhammad Farid PY - 2022 DA - 2022/11/15 TI - Analysis of Selective Exposure Cluster in the Covid-19 Vaccine Information Network on Twitter BT - Proceedings of the International Conference on Communication, Policy and Social Science (InCCluSi 2022) PB - Atlantis Press SP - 454 EP - 465 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-494069-07-7_51 DO - 10.2991/978-2-494069-07-7_51 ID - Hasanuddin2022 ER -