scholarly journals COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data (Preprint)

2020 ◽  
Author(s):  
Wasim Ahmed ◽  
Josep Vidal-Alaball ◽  
Joseph Downing ◽  
Francesc López Seguí
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
United Kingdom ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Conspiracy Theory ◽  
Fake News ◽  
The United Kingdom ◽  
Twitter Data

BACKGROUND Since the beginning of December 2019, the coronavirus disease (COVID-19) has spread rapidly around the world, which has led to increased discussions across online platforms. These conversations have also included various conspiracies shared by social media users. Amongst them, a popular theory has linked 5G to the spread of COVID-19, leading to misinformation and the burning of 5G towers in the United Kingdom. The understanding of the drivers of fake news and quick policies oriented to isolate and rebate misinformation are keys to combating it. OBJECTIVE The aim of this study is to develop an understanding of the drivers of the 5G COVID-19 conspiracy theory and strategies to deal with such misinformation. METHODS This paper performs a social network analysis and content analysis of Twitter data from a 7-day period (Friday, March 27, 2020, to Saturday, April 4, 2020) in which the #5GCoronavirus hashtag was trending on Twitter in the United Kingdom. Influential users were analyzed through social network graph clusters. The size of the nodes were ranked by their betweenness centrality score, and the graph’s vertices were grouped by cluster using the Clauset-Newman-Moore algorithm. The topics and web sources used were also examined. RESULTS Social network analysis identified that the two largest network structures consisted of an isolates group and a broadcast group. The analysis also revealed that there was a lack of an authority figure who was actively combating such misinformation. Content analysis revealed that, of 233 sample tweets, 34.8% (n=81) contained views that 5G and COVID-19 were linked, 32.2% (n=75) denounced the conspiracy theory, and 33.0% (n=77) were general tweets not expressing any personal views or opinions. Thus, 65.2% (n=152) of tweets derived from nonconspiracy theory supporters, which suggests that, although the topic attracted high volume, only a handful of users genuinely believed the conspiracy. This paper also shows that fake news websites were the most popular web source shared by users; although, YouTube videos were also shared. The study also identified an account whose sole aim was to spread the conspiracy theory on Twitter. CONCLUSIONS The combination of quick and targeted interventions oriented to delegitimize the sources of fake information is key to reducing their impact. Those users voicing their views against the conspiracy theory, link baiting, or sharing humorous tweets inadvertently raised the profile of the topic, suggesting that policymakers should insist in the efforts of isolating opinions that are based on fake news. Many social media platforms provide users with the ability to report inappropriate content, which should be used. This study is the first to analyze the 5G conspiracy theory in the context of COVID-19 on Twitter offering practical guidance to health authorities in how, in the context of a pandemic, rumors may be combated in the future.

scholarly journals COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data

10.2196/19458 ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. e19458 ◽  
Author(s):  
Wasim Ahmed ◽  
Josep Vidal-Alaball ◽  
Joseph Downing ◽  
Francesc López Seguí
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
United Kingdom ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Conspiracy Theory ◽  
Fake News ◽  
The United Kingdom ◽  
Twitter Data

Background Since the beginning of December 2019, the coronavirus disease (COVID-19) has spread rapidly around the world, which has led to increased discussions across online platforms. These conversations have also included various conspiracies shared by social media users. Amongst them, a popular theory has linked 5G to the spread of COVID-19, leading to misinformation and the burning of 5G towers in the United Kingdom. The understanding of the drivers of fake news and quick policies oriented to isolate and rebate misinformation are keys to combating it. Objective The aim of this study is to develop an understanding of the drivers of the 5G COVID-19 conspiracy theory and strategies to deal with such misinformation. Methods This paper performs a social network analysis and content analysis of Twitter data from a 7-day period (Friday, March 27, 2020, to Saturday, April 4, 2020) in which the #5GCoronavirus hashtag was trending on Twitter in the United Kingdom. Influential users were analyzed through social network graph clusters. The size of the nodes were ranked by their betweenness centrality score, and the graph’s vertices were grouped by cluster using the Clauset-Newman-Moore algorithm. The topics and web sources used were also examined. Results Social network analysis identified that the two largest network structures consisted of an isolates group and a broadcast group. The analysis also revealed that there was a lack of an authority figure who was actively combating such misinformation. Content analysis revealed that, of 233 sample tweets, 34.8% (n=81) contained views that 5G and COVID-19 were linked, 32.2% (n=75) denounced the conspiracy theory, and 33.0% (n=77) were general tweets not expressing any personal views or opinions. Thus, 65.2% (n=152) of tweets derived from nonconspiracy theory supporters, which suggests that, although the topic attracted high volume, only a handful of users genuinely believed the conspiracy. This paper also shows that fake news websites were the most popular web source shared by users; although, YouTube videos were also shared. The study also identified an account whose sole aim was to spread the conspiracy theory on Twitter. Conclusions The combination of quick and targeted interventions oriented to delegitimize the sources of fake information is key to reducing their impact. Those users voicing their views against the conspiracy theory, link baiting, or sharing humorous tweets inadvertently raised the profile of the topic, suggesting that policymakers should insist in the efforts of isolating opinions that are based on fake news. Many social media platforms provide users with the ability to report inappropriate content, which should be used. This study is the first to analyze the 5G conspiracy theory in the context of COVID-19 on Twitter offering practical guidance to health authorities in how, in the context of a pandemic, rumors may be combated in the future.

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.

scholarly journals A Social Network Analysis of Tweets Related to Masks during the COVID-19 Pandemic

2020 ◽  
Vol 17 (21) ◽  
pp. 8235
Author(s):  
Wasim Ahmed ◽  
Josep Vidal-Alaball ◽  
Francesc Lopez Segui ◽  
Pedro A. Moreno-Sánchez
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Communication Channel ◽  
The Public ◽  
Twitter Data ◽  
Wide Range ◽  
Media Research ◽  
Systematic Random Sample

Background: High compliance in wearing a mask is a crucial factor for stopping the transmission of COVID-19. Since the beginning of the pandemic, social media has been a key communication channel for citizens. This study focused on analyzing content from Twitter related to masks during the COVID-19 pandemic. Methods: Twitter data were collected using the keyword “mask” from 27 June 2020 to 4 July 2020. The total number of tweets gathered were n = 452,430. A systematic random sample of 1% (n = 4525) of tweets was analyzed using social network analysis. NodeXL (Social Media Research Foundation, California, CA, USA) was used to identify users ranked influential by betweenness centrality and was used to identify key hashtags and content. Results: The overall shape of the network resembled a community network because there was a range of users conversing amongst each other in different clusters. It was found that a range of accounts were influential and/or mentioned within the network. These ranged from ordinary citizens, politicians, and popular culture figures. The most common theme and popular hashtags to emerge from the data encouraged the public to wear masks. Conclusion: Towards the end of June 2020, Twitter was utilized by the public to encourage others to wear masks and discussions around masks included a wide range of users.

Richard Thomas Lowe (1802–1874) and his correspondence networks: botanical exchanges from Madeira

2021 ◽  
Vol 48 (2) ◽  
pp. 377-395
Author(s):  
S. Mesquita ◽  
M. Menezes De Sequeira ◽  
C. Castel-Branco
Keyword(s):  
United Kingdom ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Scientific Knowledge ◽  
Scientific Communication ◽  
Natural Sciences ◽  
The United Kingdom ◽  
Correspondence Networks

The growth of scientific knowledge in the natural sciences in the nineteenth century to a large extent depended on networking and communication between naturalists. Our case-study illustrates such forms of scientific communication using a social network analysis (SNA) approach for studying the relationships of the Reverend Richard Thomas Lowe, an English naturalist who lived in Madeira from 1826 to 1852, and continued to visit until his death in a shipwreck in 1874. During his lifetime, he established a network of contacts mainly in the United Kingdom and in Madeira, which enabled him to develop and publish his pioneering work on the local flora, including A manual flora of Madeira and the adjacent islands of Porto Santo and the Desertas.

scholarly journals Implementation of Social Network Analysis in the Spread of Natuna Issues on Twitter

2021 ◽  
Vol 4 (1) ◽  
pp. 64-72
Author(s):  
Ashif Dzilfiqar Thayyibi ◽  
◽  
Juliana Mansur ◽  
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Analysis Method ◽  
Twitter Data ◽  
Internet Users ◽  
The Social ◽  
Collection Period ◽  
Society Today

Currently, the growth of internet users has been accompanied by the development of applications that support interaction among users, which is called social media. One of the popular social media in society today is twitter. Data on Twitter can be presented in a graph structure visualization in nodes that represent actors and edges that represent relationships between actors. In an effort to find the most influential actors and actors who interact the most in spreading the Natuna topic on social media twitter, an analysis will be carried out using the Social Network Analysis method using the Degree Centrality approach. The data used in this study were taken from December 20, 2019 at 00.00 WIB to January 7, 2020 at 10.00 WIB consisting of 71,477 nodes and 147066 edges. The results of this study can be concluded that the @susipudjiastuti account is the most influential actor and plays an important role in social networking because the @susipudjiastuti account is the most linked account with 29755 links. Meanwhile, the @ shaktia704 account was the most active account during the data collection period, which reached 259 links.

scholarly journals EXAMINING THE INFORMATION DISSEMINATION PROCESS ON SOCIAL MEDIA DURING THE MALAYSIA 2014 FLOODS USING SOCIAL NETWORK ANALYSIS (SNA)

2017 ◽  
Author(s):  
Abdus-Samad Temitope Olanrewaju ◽  
Rahayu Ahmad
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information Dissemination ◽  
Governmental Organization ◽  
The Social ◽  
Dissemination Process ◽  
Information Providers

This article is based on a study which examined the information dissemination process on the social media during the Malaysia 2014 floods by employing the Social Network Analysis. Specifically, the study analyzed the type of network structure formed and its density, the influential people involved, and the kind of information shared during the flood. The data was collected from a non-governmental organization fan page (NGOFP) and a significant civilian fan page (ICFP) on Facebook using NodeXL. The two datasets contained 296 posts which generated different network structures based on the state of the flood, information available, and the needs of the information. Through content analysis, five common themes emerged from the information exchanges for both fan pages which helped in providing material and psychological support to the flood victims. However, only 5% of the networks’ population served as information providers, and this prompted the need for more active participation especially from organizations with certified information. Based on the findings presented and elaborated, this article concluded by stating the implications and recommendations of the study conducted.  

ANALISIS PERINGKAT TOP BRAND OJEK ONLINE MENGGUNAKAN JEJARING SOSIAL PERCAKAPAN TWITTER

2019 ◽  
Vol 24 (2) ◽  
pp. 88-104
Author(s):  
Ilham Aminudin ◽  
Dyah Anggraini
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Path Length ◽  
Average Path Length ◽  
Average Degree ◽  
Clustering Coefficient ◽  
R Programming

Banyak bisnis mulai muncul dengan melibatkan pengembangan teknologi internet. Salah satunya adalah bisnis di aplikasi berbasis penyedia layanan di bidang moda transportasi berbasis online yang ternyata dapat memberikan solusi dan menjawab berbagai kekhawatiran publik tentang layanan transportasi umum. Kemacetan lalu lintas di kota-kota besar dan ketegangan publik dengan keamanan transportasi umum diselesaikan dengan adanya aplikasi transportasi online seperti Grab dan Gojek yang memberikan kemudahan dan kenyamanan bagi penggunanya Penelitian ini dilakukan untuk menganalisa keaktifan percakapan brand jasa transportasi online di jejaring sosial Twitter berdasarkan properti jaringan. Penelitian dilakukan dengan dengan mengambil data dari percakapan pengguna di social media Twitter dengan cara crawling menggunakan Bahasa pemrograman R programming dan software R Studio dan pembuatan model jaringan dengan software Gephy. Setelah itu data dianalisis menggunakan metode social network analysis yang terdiri berdasarkan properti jaringan yaitu size, density, modularity, diameter, average degree, average path length, dan clustering coefficient dan nantinya hasil analisis akan dibandingkan dari setiap properti jaringan kedua brand jasa transportasi Online dan ditentukan strategi dalam meningkatkan dan mempertahankan keaktifan serta tingkat kehadiran brand jasa transportasi online, Grab dan Gojek.

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