scholarly journals Education for Sustainable Development and Climate Change Education: The Potential of Social Network Analysis Based on Twitter Data

2019 ◽  
Vol 11 (19) ◽  
pp. 5499 ◽  
Author(s):  
Goritz ◽  
Kolleck ◽  
Jörgens
Keyword(s):  
Climate Change ◽  
Sustainable Development ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
International Organizations ◽  
Governance Structure ◽  
Education For Sustainable Development ◽  
Climate Change Education ◽  
Twitter Data

Education is considered an essential tool for achieving sustainability-related goals. In this regard, education for sustainable development (ESD) and climate change education (CCE) have become prominent concepts. The central characteristics of both concepts influence the non-hierarchical network governance structure that has formed around them: (1) their international origin, (2) the conceptual ambiguity that surrounds them, and (3) the limited implementing power of international organizations who developed these concepts. Hence, networks are essential to ESD and CCE, however, only few studies have used social network analysis (SNA) techniques to analyze their governance structure. The aim of this article is to illustrate how to use SNA, based on Twitter data, as an approach to examine the governance structure that has developed around ESD and CCE. We conduct an illustrative SNA, using Twitter data during three global climate change summits (2015-2017) to examine CCE-specific debates and identify actors exerting the most influence. We find that international organizations and international treaty secretariats are most influential across all years of the analysis and, moreover, are represented most often. These findings show that using SNA based on Twitter data offers promising possibilities to better understand the governance structure and processes around both concepts.

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 literature review on forest bioeconomy with a bibliometric network analysis

2020 ◽  
Vol 66 (No. 7) ◽  
pp. 265-279 ◽  
Author(s):  
Alessandro Paletto ◽  
Ilaria Biancolillo ◽  
Jacques Bersier ◽  
Michael Keller ◽  
Manuela Romagnoli
Keyword(s):  
Climate Change ◽  
Sustainable Development ◽  
Social Network ◽  
Network Analysis ◽  
Climate Change Mitigation ◽  
Scientific Literature ◽  
Time Frame ◽  
Ecosystem Degradation ◽  
Global Challenges ◽  
Change Mitigation

Over the last couple of decades, many peer-reviewed publications focused on the bioeconomy, which it is frequently argued to be a key part of the solution to global challenges (climate change, ecosystem degradation). This study investigates the scientific literature on forest bioeconomy by applying a social network analysis to the bibliometric science. The bibliometric network analysis was performed over the time-frame of 2003–2020 to provide an overview on the main aspects characterising the forest bioeconomy issue. The results show that 225 documents on forest bioeconomy were published by 567 organisations from 44 countries. Finland and Canada are the two most productive countries with 32.8% and 12.7% of forest bioeconomy documents respectively. The co-occurrence network map of the keywords shows that the forest bioeconomy is related to three main concepts: sustainable development, bioenergy production, climate change mitigation.

scholarly journals Who Is Connected with Whom? A Social Network Analysis of Institutional Interactions in the European CCA and DRR Landscape

2020 ◽  
Vol 12 (3) ◽  
pp. 1275 ◽  
Author(s):  
Eleni Karali ◽  
Dragana Bojovic ◽  
Gabriela Michalek ◽  
Carlo Giupponi ◽  
Reimund Schwarze
Keyword(s):  
Climate Change ◽  
Cluster Analysis ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Climate Adaptation ◽  
Qualitative Interviews ◽  
Climate Change Impacts ◽  
Vision Statements ◽  
European Climate

Communication and collaboration are critical for designing and implementing responses to climate change impacts and related disasters. This acknowledgement has increased interest in understanding social and institutional networks for climate change adaptation (CCA) and disaster risk reduction (DRR). In this study, we used Social Network Analysis (SNA) to explore institutional interactions within and across the communities of the aforementioned domains in Europe. Firstly, we investigated the type and intensity of interactions. We calculated SNA metrics to assess the roles of different actors and applied cluster analysis to identify actors with similar patterns of connections. SNA showed that communication is often more intensive within the two communities, while collaboration is frequent around topics related to both CCA and DRR. Cluster analysis revealed that actors tied with DRR were more closely connected, while actors tied with CCA and those with mixed connections showed no obvious clustering affinity. The European Climate Adaptation Platform, Climate-ADAPT, had the highest value for various SNA metrics, reflecting its popularity in the network and its potential for enhancing interactions among its actors. Finally, SNA was complemented by qualitative interviews, which emphasised the importance of connecting CCA and DRR in organisational mission and vision statements.

Sign in / Sign up

Export Citation Format

Share Document