2017
DOI: 10.1136/bmjopen-2017-016869
|View full text |Cite
|
Sign up to set email alerts
|

Comparing human papillomavirus vaccine concerns on Twitter: a cross-sectional study of users in Australia, Canada and the UK

Abstract: ObjectiveOpposition to human papillomavirus (HPV) vaccination is common on social media and has the potential to impact vaccine coverage. This study aims to conduct an international comparison of the proportions of tweets about HPV vaccines that express concerns, the types of concerns expressed and the social connections among users posting about HPV vaccines in Australia, Canada and the UK.DesignUsing a cross-sectional design, an international comparison of English language tweets about HPV vaccines and socia… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
2

Citation Types

0
51
1
2

Year Published

2018
2018
2024
2024

Publication Types

Select...
6
1

Relationship

1
6

Authors

Journals

citations
Cited by 50 publications
(55 citation statements)
references
References 76 publications
0
51
1
2
Order By: Relevance
“…4,11,16 Other social influences, including by a partner, family, friends, or online social network, can also influence parents' decision. 13,[16][17][18] It is likely that these factors have varying impact on parents depending on where they are in the decision-making process, which is obscured in much previous research investigating vaccination as a binary outcome (vaccinated or not). Literature on vaccine hesitancy highlights many reasons a parent may delay or refuse vaccination for their child.…”
Section: Introductionmentioning
confidence: 99%
“…4,11,16 Other social influences, including by a partner, family, friends, or online social network, can also influence parents' decision. 13,[16][17][18] It is likely that these factors have varying impact on parents depending on where they are in the decision-making process, which is obscured in much previous research investigating vaccination as a binary outcome (vaccinated or not). Literature on vaccine hesitancy highlights many reasons a parent may delay or refuse vaccination for their child.…”
Section: Introductionmentioning
confidence: 99%
“…In a comparison between the United Kingdom, Canada, and Australia, Twitter users who were critical of HPV vaccines were found to be better connected across countries compared to users who posted other HPV vaccine information. 32 The attention of Twitter users in the United States was more likely to be consumed by North American stories presented in the mass media. 34 While these media-based controversies were not as dominant in the information diets of Australian Twitter users, news media appears to play a key role in shaping what people may have seen.…”
Section: Discussionmentioning
confidence: 99%
“…33 Topic modelling is applied by specifying in advance the number of topics that should be used to represent the set of documents but does not require the pre-specification of the nature of the topics, as would be typical of a supervised machine learning approach aiming to label tweets according to a predefined set of themes, such as Health Belief Model constructs. 32 We selected 30 topics based on a previous analysis of the clustering of topics within online communities, where we found that 30 exhibited the strongest levels of topic clustering. 33 Because topics are not specified in advance and topic modelling is not a supervised machine learning method, there is no way to objectively measure whether the topics represented within a tweet are consistent with the topics represented in other tweets assigned to the same cluster.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Twitter has been used extensively to study vaccine narratives, including those related to HPV, measles, and influenza [ 19 - 22 ]. Given Twitter’s user base of over 500 million and publicly available posts on HPV, it is a strategic site for health communicators to track HPV sentiment and target HPV vaccine messaging [ 23 - 25 ]. Massey et al examined tweet sentiment and content for 193,379 tweets from August 1, 2014 to July 31, 2015; positive tweets were more likely to mention prevention, whereas negative tweets increased the focus on side effects [ 20 ].…”
Section: Introductionmentioning
confidence: 99%