TY - GEN
T1 - Knowledge Extraction About Covid Variant in Social Media (Twitter) Using Social Network Analysis (SNA) and Latent Dirichlet Allocation (LDA)
AU - Purnama, Anton Ade
AU - Saifunas, Arsad
AU - Sensuse, Dana Indra
AU - Safitri, And Nadya
N1 - Publisher Copyright:
© 2023 American Institute of Physics Inc.. All rights reserved.
PY - 2023/12/28
Y1 - 2023/12/28
N2 - When the coronavirus disease 2019 (COVID-19) pandemic became a major global health disaster, evidence that SARS-CoV-2 might mutate grew; at this time, many SARS-CoV-2 variants are circulating globally. The information about Covid variants is spread on social media such as Twitter. It may disseminate fake news or incorrect information if the major participants in spreading Covid variations are not users with knowledge of the topic, and it may drive an individual to disregard government advice about social distance and other public health actions. The purposes of the research are to identify key players in the spreading of that information using the Social Network method Analyst (SNA) on the social network Twitter and to know what information and topics are contained in the Covid variant tweets using Latent Dirichlet Allocation (LDA). Hashtag #covidvariant is used to collect Twitter data using Twitter API from November 21st to December 6th, 2021. The Twitter API returned 47,124 tweets to be analyzed. The result of this research found that the key players are the accounts that have knowledge of Covid variants, and 10 big topics shared on Twitter regarding Covid variants. Most key players that are found are India Today, Doctor Soumya, POTUS, and WHO. The top 10 big topics that are shared on Twitter regarding Covid variants are lockdown, travel restriction, India's concern about Covid mutation, a new Covid variant in Africa, vaccine booster for Omicron, wearing a cloth face mask, Omicron case in Maharashtra, Joe Biden's statement about Omicron, Omicron impact to the business, unvaccinated kid case.
AB - When the coronavirus disease 2019 (COVID-19) pandemic became a major global health disaster, evidence that SARS-CoV-2 might mutate grew; at this time, many SARS-CoV-2 variants are circulating globally. The information about Covid variants is spread on social media such as Twitter. It may disseminate fake news or incorrect information if the major participants in spreading Covid variations are not users with knowledge of the topic, and it may drive an individual to disregard government advice about social distance and other public health actions. The purposes of the research are to identify key players in the spreading of that information using the Social Network method Analyst (SNA) on the social network Twitter and to know what information and topics are contained in the Covid variant tweets using Latent Dirichlet Allocation (LDA). Hashtag #covidvariant is used to collect Twitter data using Twitter API from November 21st to December 6th, 2021. The Twitter API returned 47,124 tweets to be analyzed. The result of this research found that the key players are the accounts that have knowledge of Covid variants, and 10 big topics shared on Twitter regarding Covid variants. Most key players that are found are India Today, Doctor Soumya, POTUS, and WHO. The top 10 big topics that are shared on Twitter regarding Covid variants are lockdown, travel restriction, India's concern about Covid mutation, a new Covid variant in Africa, vaccine booster for Omicron, wearing a cloth face mask, Omicron case in Maharashtra, Joe Biden's statement about Omicron, Omicron impact to the business, unvaccinated kid case.
UR - http://www.scopus.com/inward/record.url?scp=85182365339&partnerID=8YFLogxK
U2 - 10.1063/5.0181952
DO - 10.1063/5.0181952
M3 - Conference contribution
AN - SCOPUS:85182365339
T3 - AIP Conference Proceedings
BT - AIP Conference Proceedings
A2 - Jusman, Yessi
A2 - Zaki, Ahmad
A2 - Damarjati, Cahya
PB - American Institute of Physics Inc.
T2 - 3rd International Conference on Information Technology and Advanced Mechanical and Electrical Engineering, ICITAMEE 2022
Y2 - 20 July 2022 through 21 July 2022
ER -