scholarly journals The Visual Vaccine Debate on Twitter: A Social Network Analysis

2020 ◽  
Vol 8 (2) ◽  
pp. 364-375 ◽  
Author(s):  
Elena Milani ◽  
Emma Weitkamp ◽  
Peter Webb
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Health Professionals ◽  
Sources Of Information ◽  
Digital Environments ◽  
Vaccine Information ◽  
Vaccine Debate ◽  
Textual Content ◽  
Insight Into

Pro- and anti-vaccination users use social media outlets, such as Twitter, to join conversations about vaccines, disseminate information or misinformation about immunization, and advocate in favour or against vaccinations. These users not only share textual content, but also images to emphasise their messages and influence their audiences. Though previous studies investigated the content of vaccine images, there is little research on how these visuals are distributed in digital environments. Therefore, this study explored how images related to vaccination are shared on Twitter to gain insight into the communities and networks formed around their dissemination. Moreover, this research also investigated who influences the distribution of vaccine images, and could be potential gatekeepers of vaccination information. We conducted a social network analysis on samples of tweets with images collected in June, September and October 2016. In each dataset, pro- and anti-vaccination users formed two polarised networks that hardly interacted with each other, and disseminated images among their members differently. The anti-vaccination users frequently retweeted each other, strengthening their relationships, making the information redundant within their community, and confirming their beliefs against immunisation. The pro-vaccine users, instead, formed a fragmented network, with loose but strategic connections that facilitated networking and the distribution of new vaccine information. Moreover, while the pro-vaccine gatekeepers were non-governmental organisations or health professionals, the anti-vaccine ones were activists and/or parents. Activists and parents could potentially be considered as alternative but trustworthy sources of information enabling them to disseminate misinformation about vaccinations.

scholarly journals Improvised Music in Berlin 2012-13: A Brief Ethnographic Portrait

2016 ◽  
Vol 10 (2) ◽  
Author(s):  
Tom Arthurs
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Structure ◽  
Point Of View ◽  
Music Making ◽  
Improvised Music ◽  
Phd Thesis ◽  
Point Of Departure ◽  
Insight Into

This paper uses approaches from ethnography and Social Network Analysis to provide a brief insight into the practical, economic and social structure of Berlin’s Improvised Music scene during 2012 and 2013. The findings presented here address imbalances of gender and race, and highlight the (often difficult) financial reality of a life in Improvised Music. Audience, venues and performers are portrayed in order to provide an entry point for those unfamiliar with Improvised Music communities, and to offer an empirically researched point of departure for those already acquainted with such musicians and practices. This paper is an adaptation of parts of my PhD thesis “The Secret Gardeners: An Ethnography of Improvised Music in Berlin (2012-13),” which addresses the aesthetics, ideologies and practicalities of contemporary European Improvised Music-making from the point of view of 34 key practitioners and “expert” listeners.

scholarly journals Using Google Maps to Show the Pattern of International Co-Author Collaboration in Pharmaceutics

2018 ◽  
pp. 1-9
Keyword(s):  
Drug Delivery ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Graphical Representations ◽  
Deep Insight ◽  
Microsoft Excel ◽  
Google Maps ◽  
Future Studies ◽  
Insight Into

Objective: To understand international co-author collaboration in pharmaceutics and to visualize results by Google maps and social network analysis (SNA). Methods: Selecting 311 abstracts from the Medline based on keyword pharmaceutics [journal], we reported following features of pharmaceutics: (1) nation distribution across continents; (2) main keywords frequently displayed in papers; (3) the eminent author in pharmaceutics. We programmed Microsoft Excel VBA for extracting data from Medline. Google Maps and SNA Pajek software show graphical representations of pharmaceutics. Results: We found that (1) the most number of papers in nations are from U.S.(81, 16.05%) and Japan(34, 10.93%); (2) the most linked keywords are Pharmacokinetics and drug delivery; (3) the eminent authors are Muhammad Sohail Arshad(UK) and Takeshi Yokoo(Japan). Conclusion: Social network analysis provides wide and deep insight into relationships of entities we interested. The results drawn from Google maps can provide more information to future studies in academics.

scholarly journals COVID-19 and the “Film Your Hospital” Conspiracy Theory: Social Network Analysis of Twitter Data (Preprint)

2020 ◽  
Author(s):  
Wasim Ahmed ◽  
Francesc López Seguí ◽  
Josep Vidal-Alaball ◽  
Matthew S Katz
Keyword(s):  
Public Health ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information Source ◽  
Conspiracy Theory ◽  
Sources Of Information ◽  
Data Set ◽  
Conspiracy Theories ◽  
Twitter Data

BACKGROUND During the COVID-19 pandemic, a number of conspiracy theories have emerged. A popular theory posits that the pandemic is a hoax and suggests that certain hospitals are “empty.” Research has shown that accepting conspiracy theories increases the likelihood that an individual may ignore government advice about social distancing and other public health interventions. Due to the possibility of a second wave and future pandemics, it is important to gain an understanding of the drivers of misinformation and strategies to mitigate it. OBJECTIVE This study set out to evaluate the #FilmYourHospital conspiracy theory on Twitter, attempting to understand the drivers behind it. More specifically, the objectives were to determine which online sources of information were used as evidence to support the theory, the ratio of automated to organic accounts in the network, and what lessons can be learned to mitigate the spread of such a conspiracy theory in the future. METHODS Twitter data related to the #FilmYourHospital hashtag were retrieved and analyzed using social network analysis across a 7-day period from April 13-20, 2020. The data set consisted of 22,785 tweets and 11,333 Twitter users. The Botometer tool was used to identify accounts with a higher probability of being bots. RESULTS The most important drivers of the conspiracy theory are ordinary citizens; one of the most influential accounts is a Brexit supporter. We found that YouTube was the information source most linked to by users. The most retweeted post belonged to a verified Twitter user, indicating that the user may have had more influence on the platform. There was a small number of automated accounts (bots) and deleted accounts within the network. CONCLUSIONS Hashtags using and sharing conspiracy theories can be targeted in an effort to delegitimize content containing misinformation. Social media organizations need to bolster their efforts to label or remove content that contains misinformation. Public health authorities could enlist the assistance of influencers in spreading antinarrative content.

scholarly journals COVID-19 and the “Film Your Hospital” Conspiracy Theory: Social Network Analysis of Twitter Data

10.2196/22374 ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. e22374 ◽  
Author(s):  
Wasim Ahmed ◽  
Francesc López Seguí ◽  
Josep Vidal-Alaball ◽  
Matthew S Katz
Keyword(s):  
Public Health ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information Source ◽  
Conspiracy Theory ◽  
Sources Of Information ◽  
Data Set ◽  
Conspiracy Theories ◽  
Twitter Data

Background During the COVID-19 pandemic, a number of conspiracy theories have emerged. A popular theory posits that the pandemic is a hoax and suggests that certain hospitals are “empty.” Research has shown that accepting conspiracy theories increases the likelihood that an individual may ignore government advice about social distancing and other public health interventions. Due to the possibility of a second wave and future pandemics, it is important to gain an understanding of the drivers of misinformation and strategies to mitigate it. Objective This study set out to evaluate the #FilmYourHospital conspiracy theory on Twitter, attempting to understand the drivers behind it. More specifically, the objectives were to determine which online sources of information were used as evidence to support the theory, the ratio of automated to organic accounts in the network, and what lessons can be learned to mitigate the spread of such a conspiracy theory in the future. Methods Twitter data related to the #FilmYourHospital hashtag were retrieved and analyzed using social network analysis across a 7-day period from April 13-20, 2020. The data set consisted of 22,785 tweets and 11,333 Twitter users. The Botometer tool was used to identify accounts with a higher probability of being bots. Results The most important drivers of the conspiracy theory are ordinary citizens; one of the most influential accounts is a Brexit supporter. We found that YouTube was the information source most linked to by users. The most retweeted post belonged to a verified Twitter user, indicating that the user may have had more influence on the platform. There was a small number of automated accounts (bots) and deleted accounts within the network. Conclusions Hashtags using and sharing conspiracy theories can be targeted in an effort to delegitimize content containing misinformation. Social media organizations need to bolster their efforts to label or remove content that contains misinformation. Public health authorities could enlist the assistance of influencers in spreading antinarrative content.

Dynamic Social Network Mining

2013 ◽  
pp. 122-144
Author(s):  
Luca Cagliero ◽  
Alessandro Fiori
Keyword(s):  
Data Mining ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Knowledge Discovery ◽  
Network Mining ◽  
Social Network Mining ◽  
Dynamic Social Network ◽  
Main Work ◽  
Insight Into

This Chapter overviews most recent data mining approaches proposed in the context of social network analysis. In particular, it aims at classifying the proposed approaches based on both the adopted mining strategies and their suitability for supporting knowledge discovery in a dynamic context. To provide a thorough insight into the proposed approaches, main work issues and prospects in dynamic social network analysis are also outlined.

scholarly journals Topology of the World Tourism Web

2021 ◽  
Vol 11 (5) ◽  
pp. 2253
Author(s):  
Katarina Kostelić ◽  
Marko Turk
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Structure ◽  
Biological Network ◽  
The World ◽  
Source Countries ◽  
And Diffusion ◽  
Insight Into ◽  
Diffusion Properties

The applications of social network analysis to the world tourism network are scarce, and a research update is long overdue. The goal of this research is to examine the topology of the world tourism network and to discuss the meaning of its characteristics in light of the current situation. The data used for the analysis comprise 193 target countries, 242 source countries, and 17,022 links, which is an overall 1,448,285,894 travels in 2018. Social network analysis is applied to the data to determine network topological and diffusion properties, as well as the network structure and its regularities (does it behave more as a social or a technological/biological network?). While results presented in this paper give a thorough insight into the world tourism network in the year 2018, they are only a glimpse in comparison to the possibilities for further research.

A Data Visualization Dashboard like a Game to Show Associations Between Cited-by and Similar Journals related to JMIR Serious Games: A Bibliometric Study (Preprint)

2018 ◽  
Author(s):  
Tsair-Wei Chien ◽  
Hsien-Yi Wang ◽  
Yang Shao ◽  
Willy Chou
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Serious Games ◽  
Deep Insight ◽  
The Past ◽  
The Given ◽  
Strength Of Association ◽  
Insight Into ◽  
The U.S

BACKGROUND Over 47,703 articles were found on Pubmed.com by searching for the keyword “association between[Title]” in the past. However, to date, none present the association between cited-by and similar journals related to a given journal. Authors need one effective and efficient way to find journals related to a specific journal. The strength of association between cited-by and similar journals for a given journal is required to report. OBJECTIVE This study aims (1) to present the feature of a given journal about their keyword topics and international author collaborations; (2) to show the cited-by and similar journals related to the given journal; (3) to investigate the association between their cited-by and similar journals. METHODS We obtained 85 abstracts since 2013 from Medline based on the keywords of ("JMIR Serious Games[Journal]) on June 30, 2018, and plotted the clusters, including (i) international author collaborations, (ii) keyword topics, (iii)cited-by and similar journals related to JMIR Serious Games(JSG), and (iv) association between cited-by and similar journals, on Google Maps by using social network analysis(SNA). RESULTS This study found that (1) the most number of papers are from the U.S.( 28, 32.9%) and the U.K. (11,12.9 %), the most frequently used keywords are serious games and video games; (2) the top two journals for cited-by and similar journals, respectively, are (i) JMIR mHealth uHealth(IF=4.541), J Med Internet Res (IF=4.671) and (ii) Games Health J (IF= 2.019), J Med Internet Res (IF=4.671); (3) a mild association(=0.14) exists between cited-by and similar journals related to JSG. CONCLUSIONS SNA provides deep insight into the relationships of related journals to a given journal. The results of this research can provide readers with a knowledge and concept diagram to use with future manuscript submissions to JSG. CLINICALTRIAL Not available

scholarly journals Listed Buildings as Socio-material Hybrids: Assessing Tangible and Intangible Heritage Using Social Network Analysis

2020 ◽  
Vol 5 (2) ◽  
pp. 169-190
Author(s):  
Johnathan Djabarouti
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Phenomena ◽  
Methodist Church ◽  
Built Heritage ◽  
Intangible Heritage ◽  
Grade Ii ◽  
Insight Into ◽  
Inherent Part

Immaterial manifestations of culture have received increasing attention over the past two decades. This is of particular relevance to the contemporary built heritage professional who must not only consider intangible heritage within assessments but attempt to understand its relationship with the physical building fabric. Underpinned by a ‘Practice Theory’ ontology, this research explores how social network analysis (SNA) can reveal entanglements between tangible and intangible heritage by focussing on practices and relationships. Using the Grade II* Long Street Methodist Church and Sunday School, Greater Manchester, UK, the study demonstrates how the basic use of SNA for built heritage assessment can offer a deeper insight into the significance of a listed building. The study demonstrates how SNA can support: an equality of visibility across heritage domains, a better understanding of tangible–intangible relationships and the illumination of underlying practices that sustains these relationships. Perhaps most importantly, it emphasizes the dynamic and unpredictable nature of heritage by de-emphasizing the centrality of the building within heritage assessment processes and reconceptualizing it as an inherent part of social phenomena. In doing so, it suggests one must accept the notion that socio-material practices should be considered for conservation and safeguarding, alongside the physical building itself.

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