2023
DOI: 10.1108/k-06-2022-0810
|View full text |Cite
|
Sign up to set email alerts
|

Exploring COVID-19 vaccine hesitancy and behavioral themes using social media big-data: a text mining approach

Abstract: PurposeIndia has the biggest number of active users on social media platforms, particularly Twitter. The purpose of this paper is to examine public sentiment on COVID-19 vaccines and COVID Appropriate Behaviour (CAB) by text mining (topic modeling) and network analysis supported by thematic modeling.Design/methodology/approachA sample dataset of 115,000 tweets from the Twitter platform was used to examine the perception of the COVID-19 vaccination and CAB from January 2021 to August 2021. The research applied … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
3
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
5
1
1

Relationship

0
7

Authors

Journals

citations
Cited by 7 publications
(4 citation statements)
references
References 140 publications
0
3
0
Order By: Relevance
“…That study identified various factors relating to access (e.g., location of vaccine), affordability (e.g., price of additional services), awareness (e.g., knowledge about vaccines), acceptance (e.g., perceived vaccine safety), activation (e.g., incentives), and assurance (e.g., protection) for variations in uptake. Similar applications of topic modelling include work by [ 35 , 36 , 69 , 70 ]. A number of studies have also applied sentiment analysis to social media to gauge the general sentiment and attitudes of individuals towards vaccines and vaccination efforts [ 30 , 71 74 ].…”
Section: Related Workmentioning
confidence: 92%
See 1 more Smart Citation
“…That study identified various factors relating to access (e.g., location of vaccine), affordability (e.g., price of additional services), awareness (e.g., knowledge about vaccines), acceptance (e.g., perceived vaccine safety), activation (e.g., incentives), and assurance (e.g., protection) for variations in uptake. Similar applications of topic modelling include work by [ 35 , 36 , 69 , 70 ]. A number of studies have also applied sentiment analysis to social media to gauge the general sentiment and attitudes of individuals towards vaccines and vaccination efforts [ 30 , 71 74 ].…”
Section: Related Workmentioning
confidence: 92%
“…Although there there exists a substantial body of research that have utilized social media data to examine various aspects of vaccines, much of the research have focused only on a few themes. These include analyzing misinformation campaigns and particular communities, such as the anti-vaccination movement (e.g., [ 26 , 27 ]), exploring the network interactions among hesitant community members (e.g., [ 28 , 29 ]), understanding sentiments towards vaccines (e.g., [ 30 , 31 ]) and the role of social media in influencing public attitude towards them (e.g., [ 32 34 ]), and analyzing topics of discourse surrounding vaccines (e.g., [ 35 , 36 ]). However, the potential of social media data as a viable proxy for understanding vaccine hesitancy and its underlying determinants, particularly when juxtaposed against traditional survey data, remains an area that has garnered relatively little attention.…”
Section: Introductionmentioning
confidence: 99%
“…The specific manifestation is that when parents invest time and energy in students, but do not get the expected results, parents will have educational anxiety (Naz, 2021). Foreign scholar Spielber defines educational anxiety as a kind of state anxiety (Yadav & Sagar, 2023). Wang Hongcai was the first person in China to propose the concept of parental educational anxiety (Wang, 2023).…”
Section: Parent Education Anxiety Conceptmentioning
confidence: 99%
“…Other determinants including lack of knowledge, government distrust, skepticism about vaccine development, efficacy concerns, exposure experience, coronaphobia, and workplace mandates also predict vaccine uptake [ 11 - 13 ]. As social media becomes increasingly significant for public communication, social media adaptivity, information availability, and health care infrastructure capabilities are also influential for vaccination decisions [ 14 ].…”
Section: Introductionmentioning
confidence: 99%