The Experts below are selected from a list of 25848 Experts worldwide ranked by ideXlab platform

Francesc Lopez Segui - One of the best experts on this subject based on the ideXlab platform.

  • covid 19 and the 5g conspiracy theory Social Network analysis of twitter data
    Journal of Medical Internet Research, 2020
    Co-Authors: Wasim Ahmed, Josep Vidalalaball, Joseph Downing, Francesc Lopez Segui
    Abstract:

    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.

  • dangerous messages or satire analysing the conspiracy theory linking 5g to covid 19 through Social Network analysis
    Journal of Medical Internet Research, 2020
    Co-Authors: Wasim Ahmed, Josep Vidalalaball, Joseph Downing, Francesc Lopez Segui
    Abstract:

    BACKGROUND: Since the beginning of December 2019 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 key to combating it OBJECTIVE: 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 27 March 2020 to Saturday 04 April 2020, in which the #5GCoronavirus hashtag was trending on Twitter in the United Kingdom Influential users are analyzed through Social Network Graph clusters The size of the nodes is ranked by their betweenness centrality score and the Graph's vertices are grouped by cluster using the Clauset-Newman-Moore algorithm Topics and Web sources utilized by users are examined RESULTS: Social Network Analysis identified that the two largest Network structures consisted of an isolates group and a broadcast group The analysis also reveals that there was a lack of authority figure who was actively combating such misinformation Content analysis reveals that only 35% of individual tweets contained views that 5G and COVID-19 were linked whereas 32% denounced the conspiracy theory and 33% were general tweets not expressing any personal views or opinions Thus, 65% of tweets derived from non-conspiracy 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 targeted interventions oriented to delegitimize the sources of fake information are 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 which are based on fake news Many Social media platforms provide users with the ability to report inappropriate content which should be utilized This study is the first to analyse 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 CLINICALTRIAL:

Wasim Ahmed - One of the best experts on this subject based on the ideXlab platform.

  • covid 19 and the 5g conspiracy theory Social Network analysis of twitter data
    Journal of Medical Internet Research, 2020
    Co-Authors: Wasim Ahmed, Josep Vidalalaball, Joseph Downing, Francesc Lopez Segui
    Abstract:

    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.

  • dangerous messages or satire analysing the conspiracy theory linking 5g to covid 19 through Social Network analysis
    Journal of Medical Internet Research, 2020
    Co-Authors: Wasim Ahmed, Josep Vidalalaball, Joseph Downing, Francesc Lopez Segui
    Abstract:

    BACKGROUND: Since the beginning of December 2019 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 key to combating it OBJECTIVE: 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 27 March 2020 to Saturday 04 April 2020, in which the #5GCoronavirus hashtag was trending on Twitter in the United Kingdom Influential users are analyzed through Social Network Graph clusters The size of the nodes is ranked by their betweenness centrality score and the Graph's vertices are grouped by cluster using the Clauset-Newman-Moore algorithm Topics and Web sources utilized by users are examined RESULTS: Social Network Analysis identified that the two largest Network structures consisted of an isolates group and a broadcast group The analysis also reveals that there was a lack of authority figure who was actively combating such misinformation Content analysis reveals that only 35% of individual tweets contained views that 5G and COVID-19 were linked whereas 32% denounced the conspiracy theory and 33% were general tweets not expressing any personal views or opinions Thus, 65% of tweets derived from non-conspiracy 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 targeted interventions oriented to delegitimize the sources of fake information are 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 which are based on fake news Many Social media platforms provide users with the ability to report inappropriate content which should be utilized This study is the first to analyse 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 CLINICALTRIAL:

Joseph Downing - One of the best experts on this subject based on the ideXlab platform.

  • covid 19 and the 5g conspiracy theory Social Network analysis of twitter data
    Journal of Medical Internet Research, 2020
    Co-Authors: Wasim Ahmed, Josep Vidalalaball, Joseph Downing, Francesc Lopez Segui
    Abstract:

    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.

  • dangerous messages or satire analysing the conspiracy theory linking 5g to covid 19 through Social Network analysis
    Journal of Medical Internet Research, 2020
    Co-Authors: Wasim Ahmed, Josep Vidalalaball, Joseph Downing, Francesc Lopez Segui
    Abstract:

    BACKGROUND: Since the beginning of December 2019 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 key to combating it OBJECTIVE: 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 27 March 2020 to Saturday 04 April 2020, in which the #5GCoronavirus hashtag was trending on Twitter in the United Kingdom Influential users are analyzed through Social Network Graph clusters The size of the nodes is ranked by their betweenness centrality score and the Graph's vertices are grouped by cluster using the Clauset-Newman-Moore algorithm Topics and Web sources utilized by users are examined RESULTS: Social Network Analysis identified that the two largest Network structures consisted of an isolates group and a broadcast group The analysis also reveals that there was a lack of authority figure who was actively combating such misinformation Content analysis reveals that only 35% of individual tweets contained views that 5G and COVID-19 were linked whereas 32% denounced the conspiracy theory and 33% were general tweets not expressing any personal views or opinions Thus, 65% of tweets derived from non-conspiracy 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 targeted interventions oriented to delegitimize the sources of fake information are 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 which are based on fake news Many Social media platforms provide users with the ability to report inappropriate content which should be utilized This study is the first to analyse 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 CLINICALTRIAL:

Josep Vidalalaball - One of the best experts on this subject based on the ideXlab platform.

  • covid 19 and the 5g conspiracy theory Social Network analysis of twitter data
    Journal of Medical Internet Research, 2020
    Co-Authors: Wasim Ahmed, Josep Vidalalaball, Joseph Downing, Francesc Lopez Segui
    Abstract:

    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.

  • dangerous messages or satire analysing the conspiracy theory linking 5g to covid 19 through Social Network analysis
    Journal of Medical Internet Research, 2020
    Co-Authors: Wasim Ahmed, Josep Vidalalaball, Joseph Downing, Francesc Lopez Segui
    Abstract:

    BACKGROUND: Since the beginning of December 2019 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 key to combating it OBJECTIVE: 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 27 March 2020 to Saturday 04 April 2020, in which the #5GCoronavirus hashtag was trending on Twitter in the United Kingdom Influential users are analyzed through Social Network Graph clusters The size of the nodes is ranked by their betweenness centrality score and the Graph's vertices are grouped by cluster using the Clauset-Newman-Moore algorithm Topics and Web sources utilized by users are examined RESULTS: Social Network Analysis identified that the two largest Network structures consisted of an isolates group and a broadcast group The analysis also reveals that there was a lack of authority figure who was actively combating such misinformation Content analysis reveals that only 35% of individual tweets contained views that 5G and COVID-19 were linked whereas 32% denounced the conspiracy theory and 33% were general tweets not expressing any personal views or opinions Thus, 65% of tweets derived from non-conspiracy 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 targeted interventions oriented to delegitimize the sources of fake information are 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 which are based on fake news Many Social media platforms provide users with the ability to report inappropriate content which should be utilized This study is the first to analyse 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 CLINICALTRIAL:

Rong Jin - One of the best experts on this subject based on the ideXlab platform.

  • publishing Social Network Graph eigenspectrum with privacy guarantees
    IEEE Transactions on Network Science and Engineering, 2020
    Co-Authors: Faraz Ahmed, Alex X. Liu, Rong Jin
    Abstract:

    Online Social Networks (OSNs) often refuse to publish their Social Network Graphs due to privacy concerns. Recently, differential privacy has become the widely accepted criteria for privacy preserving data publishing. Although some work has been done on publishing matrices with differential privacy, they are computationally unpractical as they are not designed to handle large matrices such as adjacency matrices of OSN Graphs. In this paper, we propose a random matrix approach to OSN data publishing, which achieves storage and computational efficiency by reducing dimensions of adjacency matrices and achieves differential privacy by adding a small amount of noise. Our key idea is to first project each row of an adjacency matrix into a low-dimensional space using random projection, and then perturb the projected matrix with random noise, and finally publish the perturbed and projected matrix. In this paper, we first prove that random projection plus random perturbation preserve differential privacy, and also that the random noise required to achieve differential privacy is small. We validate the proposed approach and evaluate the utility of the published data for three different applications, namely node clustering, node ranking, and node classification, using publicly available OSN Graphs of Facebook, LiveJournal, and Pokec.

  • A Random Matrix Approach to Differential Privacy and Structure Preserved Social Network Graph Publishing
    2016
    Co-Authors: Faraz Ahmed, Rong Jin, Alex X. Liu
    Abstract:

    Online Social Networks are being increasingly used for an-alyzing various societal phenomena such as epidemiology, information dissemination, marketing and sentiment flow. Popular analysis techniques such as clustering and influen-tial node analysis, require the computation of eigenvectors of the real Graph’s adjacency matrix. Recent de-anonymization attacks on Netflix and AOL datasets show that an open ac-cess to such Graphs pose privacy threats. Among the various privacy preserving models, Differential privacy provides the strongest privacy guarantees. In this paper we propose a privacy preserving mechanism for publishing Social Network Graph data, which satisfies dif-ferential privacy guarantees by utilizing a combination of theory of random matrix and that of differential privacy. The key idea is to project each row of an adjacency matrix to a low dimensional space using the random projection ap-proach and then perturb the projected matrix with random noise. We show that as compared to existing approaches for differential private approximation of eigenvectors, our ap-proach is computationally efficient, preserves the utility and satisfies differential privacy. We evaluate our approach on Social Network Graphs of Facebook, Live Journal and Pokec. The results show that even for high values of noise variance σ = 1 the clustering quality given by normalized mutual in-formation gain is as low as 0.74. For influential node discov-ery, the propose approach is able to correctly recover 80 % of the most influential nodes. We also compare our results with an approach presented in [43], which directly perturbs the eigenvector of the original data by a Laplacian noise. The results show that this approach requires a large random per-turbation in order to preserve the differential privacy, which leads to a poor estimation of eigenvectors for large Social Networks