Assessing HPV vaccination perceptions with online social media in Italy

2019 ◽  
Vol 29 (3) ◽  
pp. 453-458 ◽  
Author(s):  
Roberto Angioli ◽  
Massimo Casciello ◽  
Salvatore Lopez ◽  
Francesco Plotti ◽  
Lidia Di Minco ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Hpv Vaccine ◽  
Hpv Vaccination ◽  
Publication Date ◽  
Main Theme ◽  
Online Social Media ◽  
Trade Name ◽  
Promotional Strategies ◽  
Underlying Mechanisms

ObjectiveBecause of the widespread availability of the internet and social media, people often collect and disseminate news online making it important to understand the underlying mechanisms to steer promotional strategies in healthcare. The aim of this study is to analyze perceptions regarding the human papillomavirus (HPV) vaccine in Italy.MethodsFrom August 2015 to July 2016, articles, news, posts, and tweets were collected from social networks, posts on forums, blogs, and pictures about HPV. Using other keywords and specific semantic rules, we selected conversations presenting the negative or positive perceptions of HPV. We divided them into subgroups depending on the website, publication date, authors, main theme, and transmission modality.ResultsMost conversations occurred on social networks. Of all the conversations regarding HPV, more than 50% were about vaccination. With regard to conversations exclusively on the HPV vaccine, 47%, 32%, and 21% were positive, negative and neutral, respectively. Only 9% of the conversations mentioned the vaccine trade name and, in these conversations, perception was almost always negative. We observed many peaks in positive conversation trends compared with negative trends. The peaks were related to the web dissemination of particular news regarding HPV vaccination.ConclusionsIn this study we have shown how mass media influences the diffusion of both negative and positive perceptions about HPV vaccines and suggest better ways to inform people about the importance of HPV vaccination.

scholarly journals Round table: Online anti-vaccination movements: the role of social media in public health communications

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
Keyword(s):  
Public Health ◽  
Social Networks ◽  
Social Media ◽  
Real Time ◽  
Hpv Vaccine ◽  
Digital Health ◽  
World Health ◽  
Swine Flu ◽  
Potential Impact ◽  
The Impact

Abstract Digital health has revolutionised healthcare, with implications for understanding public reaction to health emergencies and interventions. Social media provides a space where like-minded people can share interests and concerns in real-time, regardless of their location. This can be a force for good, as platforms like Twitter can spread correct information about outbreaks, for example in the 2009 swine flu pandemic. However, social media can also disseminate incorrect information or deliberately spread misinformation leading to adverse public health sentiment and outcomes. The current issues around trust in vaccines is the best-known example. Vaccine hesitancy, traditionally linked to issues of trust, misinformation and prior beliefs, has been increasingly fueled by influential groups on social media and the Internet. Ultimately, anti-vaccination movements have the potential to lead to outbreaks of vaccine-preventable diseases, especially if refusal is concentrated locally, creating vulnerable populations. For example, 2018-19 saw a large increase in incidence of measles in the US and Europe (where cases tripled from 2017), two regions where the disease was already or almost eliminated. In 2019, the World Health Organisation listed anti-vaccination movements as one of the top 10 threats to global public health. HPV vaccination is another example of the impact of anti-vaccination movements. As viral videos originating on YouTube spread across social networks, uptake has tumbled in a number of countries, with Japan, Denmark, Colombia and Ireland being badly hit. In Japan, the government came under sufficient pressure that they de-recommended HPV vaccine, seeing an 80% uptake rate fall below 1% in 2014. There have been reports of successful interventions by national governments. A recent campaign run by the HPV Alliance (a coalition of some 35 private companies, charities and public institutions) in Ireland has seen rates below 40% back up to a national average of 75%. A combination of hard-hitting personal testimonials, social media and traditional media promoted the HPV vaccine. Despite this, systematic engagement and supranational strategies are still in the early stages of being formulated. As misleading information spread through social media and digital networks has undesirable impact on attitudes to vaccination (and uptake rates), urgent actions are required. Analysis and visualisation techniques mining data streams from social media platforms, such as Twitter, Youtube enable real-time understanding of vaccine sentiments and information flows. Through identification of key influencers and flashpoints in articles about vaccination going viral, targeted public health responses could be developed. This roundtable discussion will showcase different ways in which media and social networks, accessible in real-time provide an opportunity for detecting a change in public confidence in vaccines, for identifying users and rumors and for assessing potential impact in order to know how to best respond. Key messages Social media has significantly enhanced our understanding of anti-vaccination movements and potential impact on public health attitudes and behaviors regarding vaccination. Innovative methods of analysing social media data, from digital health, data science and computer science, have an important role in developing health promotions to counter anti-vaccination movements.

scholarly journals Social Media and Fake News in the Post-Truth Era: The Manipulation of Politics in the Election Process

2020 ◽  
pp. 177-196
Author(s):  
Turgay Yerlikaya ◽  
Seca Toker
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Presidential Elections ◽  
Political Life ◽  
Main Theme ◽  
Fake News ◽  
Election Process ◽  
Use Of Social Media ◽  
The Uk ◽  
Positive Effect

This article focuses on how virtual social networks affect socio-political life. The main theme of the article is how social networks such as Facebook and Twitter can direct voters’ electoral preferences, especially during election time, through the dissemination of manipulative content and fake news. The use of social media, which was initially thought to have a positive effect on democratization, has been extensively discussed in recent years as threat to democracy. Examples from the 2016 U.S. presidential elections, France, Brexit, Germany, the UK and Turkey will be used to illustrate the risks that social networks pose to democracy, especially during election periods.

scholarly journals Human Papillomavirus Vaccination and Social Media: Results in a Trial With Mothers of Daughters Aged 14–17

2021 ◽  
Vol 3 ◽  
Author(s):  
David B. Buller ◽  
Sherry Pagoto ◽  
Kimberly Henry ◽  
Julia Berteletti ◽  
Barbara J. Walkosz ◽  
...  
Keyword(s):  
Social Media ◽  
Human Papillomavirus ◽  
Hpv Vaccine ◽  
Hpv Vaccination ◽  
Vaccine Uptake ◽  
Drug Misuse ◽  
Relative Advantage ◽  
Control Group ◽  
Hpv Vaccines ◽  
Self Reports

Introduction: Parents acquire information about human papillomavirus (HPV) vaccines online and encounter vaccine-critical content, especially on social media, which may depress vaccine uptake. Secondary analysis in a randomized trial of a Facebook-delivered adolescent health campaign targeting mothers with posts on HPV vaccination was undertaken with the aims of (a) determining whether the pre–post-change occurred in self-reports of the mothers on HPV vaccination of their adolescent daughters; (b) describing the comments and reactions to vaccine posts; (c) exploring the relationship of campaign engagement of the mothers assessed by their comments and reactions to posts to change in the self-reports of the mothers of HPV vaccination.Materials and Methods: Mothers of daughters aged 14–17 were recruited from 34 states of the US (n = 869). A social media campaign was delivered in two Facebook private groups that differed in that 16% of posts in one were focused on indoor tanning (IT) and 16% in the other, on prescription drug misuse, assigned by randomization. In both groups, posts promoted HPV vaccination (n = 38 posts; no randomization) and vaccination for other disease (e.g., influenza, n = 49). HPV and other vaccination posts covered the need for a vaccine, the number of adolescents vaccinated, how vaccines are decreasing the infection rates, and stories of positive benefits of being vaccinated or harms from not vaccinating. Guided by social cognitive theory and diffusion of innovations theory, posts were intended to increase knowledge, perceived risk, response efficacy (i.e., a relative advantage over not vaccinated daughters), and norms for vaccination. Some vaccination posts linked to stories to capitalize on identification effects in narratives, as explained in transportation theory. All mothers received the posts on vaccination (i.e., there was no randomization). Mothers completed surveys at baseline and 12- and 18-month follow-up to assess HPV vaccine uptake by self-report measures. Reactions (such as sad, angry) and comments to each HPV-related post were counted and coded.Results: Initiation of HPV vaccination (1 dose) was reported by 63.4% of mothers at baseline, 71.3% at 12-month posttest (pre/post p < 0.001), and 73.3% at 18-month posttest (pre/post p < 0.001). Completion of HPV vaccination (two or three doses) was conveyed by 50.2% of mothers at baseline, 62.5% at 12-month posttest (pre/post p < 0.001), and 65.9% at 18-month posttest (pre/post p < 0.001). For posts on HPV vaccines, 8.1% of mothers reacted (n = 162 total), and 68.4% of posts received a reaction (63.2% like; 13.2% love, 7.9% sad). In addition, 7.6% of mothers commented (n = 122; 51 unfavorable, 68 favorable, 1 neutral), and 50.0% of these posts received a comment. There were no differences in pre–post change in vaccine status by the count of reactions or comments to HPV vaccine posts (Ps > 0.05). Baseline vaccination was associated with the valence of comments to HPV vaccine posts (7.2% of mothers whose daughters had completed the HPV series at baseline made a favorable comment but 7.6% of mothers whose daughters were unvaccinated made an unfavorable comment).Conclusion: Effective strategies are needed in social media to promote HPV vaccines and counter misinformation about and resistance to them. Mothers whose daughters complete the HPV vaccine course might be recruited as influencers on HPV vaccines, as they may be predisposed to talk favorably about the vaccine. Comments from mothers who have not been vaccinated should be monitored to ensure that they do not spread vaccine-critical misinformation. Study limitations included lack of randomization and control group, relatively small number of messages on HPV vaccines, long measurement intervals, inability to measure views of vaccination posts, reduced generalizability related to ethnicity and social media use, and use of self-reported vaccine status.Clinical Trial Registration:www.clinicaltrials.gov, identifier NCT02835807.

scholarly journals Mining HPV Vaccine Knowledge Structures of Young Adults From Reddit Using Distributional Semantics and Pathfinder Networks

2020 ◽  
Vol 27 (1) ◽  
pp. 107327481989144 ◽  
Author(s):  
Muhammad Amith ◽  
Trevor Cohen ◽  
Rachel Cunningham ◽  
Lara S. Savas ◽  
Nina Smith ◽  
...  
Keyword(s):  
Social Media ◽  
Young Adults ◽  
Hpv Vaccine ◽  
Hpv Vaccination ◽  
Semantic Relatedness ◽  
Knowledge Structures ◽  
Distributional Semantics ◽  
Online Content ◽  
Future Health ◽  
Pathfinder Networks

The human papillomavirus (HPV) vaccine protects adolescents and young adults from 9 high-risk HPV virus types that cause 90% of cervical and anal cancers and 70% of oropharyngeal cancers. This study extends our previous research analyzing online content concerning the HPV vaccination in social media platforms used by young adults, in which we used Pathfinder network scaling and methods of distributional semantics to characterize differences in knowledge organization reflected in consumer- and expert-generated online content. The current study extends this approach to evaluate HPV vaccine perceptions among young adults who populate Reddit, a major social media platform. We derived Pathfinder networks from estimates of semantic relatedness obtained by learning word embeddings from Reddit posts and compared these to networks derived from human expert estimation of the relationship between key concepts. Results revealed that users of Reddit, predominantly comprising young adults in the vaccine catch up age-group 18 through 26 years of age, perceived the HPV vaccine domain from a virus-framed perspective that could impact their lifestyle choices and that their awareness of the HPV vaccine for cancer prevention is also lacking. Further differences in knowledge structures were elucidated, with implications for future health communication initiatives.

scholarly journals Identifying Influencers in Social Networks

Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 450 ◽  
Author(s):  
Xinyu Huang ◽  
Dongming Chen ◽  
Dongqi Wang ◽  
Tao Ren
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Daily Life ◽  
Multidisciplinary Research ◽  
Multilayer Network ◽  
Online Social Media ◽  
Huge Data ◽  
Real World Datasets ◽  
Shed Light

Social network analysis is a multidisciplinary research covering informatics, mathematics, sociology, management, psychology, etc. In the last decade, the development of online social media has provided individuals with a fascinating platform of sharing knowledge and interests. The emergence of various social networks has greatly enriched our daily life, and simultaneously, it brings a challenging task to identify influencers among multiple social networks. The key problem lies in the various interactions among individuals and huge data scale. Aiming at solving the problem, this paper employs a general multilayer network model to represent the multiple social networks, and then proposes the node influence indicator merely based on the local neighboring information. Extensive experiments on 21 real-world datasets are conducted to verify the performance of the proposed method, which shows superiority to the competitors. It is of remarkable significance in revealing the evolutions in social networks and we hope this work will shed light for more and more forthcoming researchers to further explore the uncharted part of this promising field.

Rumor Detection on Twitter Using a Supervised Machine Learning Framework

2021 ◽  
pp. 452-465
Author(s):  
Hardeo Kumar Thakur ◽  
Anand Gupta ◽  
Ayushi Bhardwaj ◽  
Devanshi Verma
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Media ◽  
Supervised Machine Learning ◽  
Learning Framework ◽  
Online Social Media ◽  
Rumor Propagation ◽  
Multiple Classification ◽  
The Government ◽  
Rumor Detection

This article describes how a rumor can be defined as a circulating unverified story or a doubtful truth. Rumor initiators seek social networks vulnerable to illimitable spread, therefore, online social media becomes their stage. Hence, this misinformation imposes colossal damage to individuals, organizations, and the government, etc. Existing work, analyzing temporal and linguistic characteristics of rumors seems to give ample time for rumor propagation. Meanwhile, with the huge outburst of data on social media, studying these characteristics for each tweet becomes spatially complex. Therefore, in this article, a two-fold supervised machine-learning framework is proposed that detects rumors by filtering and then analyzing their linguistic properties. This method attempts to automate filtering by training multiple classification algorithms with accuracy higher than 81.079%. Finally, using textual characteristics on the filtered data, rumors are detected. The effectiveness of the proposed framework is shown through extensive experiments on over 10,000 tweets.

Working Adults' Buying Intention Through Online Social Network

2021 ◽  
Vol 17 (4) ◽  
pp. 92-116
Author(s):  
Syed Shah Alam ◽  
Chieh-Yu Lin ◽  
Mohd Helmi Ali ◽  
Nor Asiah Omar ◽  
Mohammad Masukujjaman
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Online Social Networks ◽  
Perceived Risk ◽  
Word Of Mouth ◽  
Online Social Network ◽  
Perceived Value ◽  
Online Social Media ◽  
Starting Point

Most businesses have online social media presence; therefore, understanding of working adult's perception on buying through online social networks is vital. The aim of this study is to examine the effect of perceived value, sociability, usability, perceived risk, trust, and e-word-of-mouth on buying intention through online social network sites. The research model for this study was developed based on the literature on information system research. This study adopted convenient sampling of non-probability sampling procedure. Data were collected through self-administered questionnaire, and PLS-based path analysis was used to analyse responses. The findings of the study shows that perceived value, sociability, usability, e-word-of-mouth, attitude, and subjective norm are significant constructs of buying intention through online social networks. This research can serve as a starting point for online shopping research through online social media while encouraging further exploration and integration addition adoption constructs.

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