LIVIVO - Search results -

Search results

Result 1 - 10 of total 12

Search options

Article ; Online: Economic bifurcations in pandemic leadership: Power in abundance or agency amid scarcity?

Uyheng, Joshua / Montiel, Cristina Jayme

The British journal of social psychology

2023 Volume 62, Issue 3, Page(s) 1534–1546

Abstract: Social psychological scholarship has emphasized the importance of effective leadership during the COVID-19 pandemic. However, the wider material contexts of these dynamics have often remained understudied. Through a critical discursive lens, this paper ... ...

Abstract	Social psychological scholarship has emphasized the importance of effective leadership during the COVID-19 pandemic. However, the wider material contexts of these dynamics have often remained understudied. Through a critical discursive lens, this paper investigates differences in the social constructions used by leaders of richer and poorer nations during the COVID-19 pandemic. We identify a sharp economic bifurcation in global discourses of pandemic leadership. Pandemic leadership in wealthier nations exercises power in abundance by mobilizing institutions and inspiring communities through discursive frames of coordination and collaboration. Conversely, pandemic leadership in poorer settings negotiates agency amid scarcity by tactically balancing resources, freedoms and dignity within discursive frames of restriction and recuperation. Implications of these findings are unpacked for understanding leadership especially during an international crisis, highlighting the need for critical sensitivities to wider societal structures for a genuinely global social psychology.
MeSH term(s)	Humans ; Leadership ; Pandemics ; COVID-19 ; Negotiating ; Psychology, Social
Language	English
Publishing date	2023-03-27
Publishing country	England
Document type	Journal Article
ZDB-ID	625325-8
ISSN	2044-8309 ; 0144-6665
ISSN (online)	2044-8309
ISSN	0144-6665
DOI	10.1111/bjso.12646
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 185: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: Characterizing network dynamics of online hate communities around the COVID-19 pandemic.

Uyheng, Joshua / Carley, Kathleen M

Applied network science

2021 Volume 6, Issue 1, Page(s) 20

Abstract: Hate speech has long posed a serious problem for the integrity of digital platforms. Although significant progress has been made in identifying hate speech in its various forms, prevailing computational approaches have tended to consider it in isolation ... ...

Abstract	Hate speech has long posed a serious problem for the integrity of digital platforms. Although significant progress has been made in identifying hate speech in its various forms, prevailing computational approaches have tended to consider it in isolation from the community-based contexts in which it spreads. In this paper, we propose a dynamic network framework to characterize hate communities, focusing on Twitter conversations related to COVID-19 in the United States and the Philippines. While average hate scores remain fairly consistent over time, hate communities grow increasingly organized in March, then slowly disperse in the succeeding months. This pattern is robust to fluctuations in the number of network clusters and average cluster size. Infodemiological analysis demonstrates that in both countries, the spread of hate speech around COVID-19 features similar reproduction rates as other COVID-19 information on Twitter, with spikes in hate speech generation at time points with highest community-level organization of hate speech. Identity analysis further reveals that hate in the US initially targets political figures, then grows predominantly racially charged; in the Philippines, targets of hate consistently remain political over time. Finally, we demonstrate that higher levels of community hate are consistently associated with smaller, more isolated, and highly hierarchical network clusters across both contexts. This suggests potentially shared structural conditions for the effective spread of hate speech in online communities even when functionally targeting distinct identity groups. Our findings bear theoretical and methodological implications for the scientific study of hate speech and understanding the pandemic's broader societal impacts both online and offline.
Language	English
Publishing date	2021-03-05
Publishing country	Switzerland
Document type	Journal Article
ISSN	2364-8228
ISSN (online)	2364-8228
DOI	10.1007/s41109-021-00362-x
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article: Mapping state-sponsored information operations with multi-view modularity clustering.

Uyheng, Joshua / Cruickshank, Iain J / Carley, Kathleen M

EPJ data science

2022 Volume 11, Issue 1, Page(s) 25

Abstract: This paper presents a new computational framework for mapping state-sponsored information operations into distinct strategic units. Utilizing a novel method called multi-view modularity clustering (MVMC), we identify groups of accounts engaged in ... ...

Abstract	This paper presents a new computational framework for mapping state-sponsored information operations into distinct strategic units. Utilizing a novel method called multi-view modularity clustering (MVMC), we identify groups of accounts engaged in distinct narrative and network information maneuvers. We then present an analytical pipeline to holistically determine their coordinated and complementary roles within the broader digital campaign. Applying our proposed methodology to disclosed Chinese state-sponsored accounts on Twitter, we discover an overarching operation to protect and manage Chinese international reputation by attacking individual adversaries (Guo Wengui) and collective threats (Hong Kong protestors), while also projecting national strength during global crisis (the COVID-19 pandemic). Psycholinguistic tools quantify variation in narrative maneuvers employing hateful and negative language against critics in contrast to communitarian and positive language to bolster national solidarity. Network analytics further distinguish how groups of accounts used network maneuvers to act as balanced operators, organized masqueraders, and egalitarian echo-chambers. Collectively, this work breaks methodological ground on the interdisciplinary application of unsupervised and multi-view methods for characterizing not just digital campaigns in particular, but also coordinated activity more generally. Moreover, our findings contribute substantive empirical insights around how state-sponsored information operations combine narrative and network maneuvers to achieve interlocking strategic objectives. This bears both theoretical and policy implications for platform regulation and understanding the evolving geopolitical significance of cyberspace.
Language	English
Publishing date	2022-04-18
Publishing country	Germany
Document type	Journal Article
ZDB-ID	2705691-0
ISSN	2193-1127
ISSN	2193-1127
DOI	10.1140/epjds/s13688-022-00338-6
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Bots and online hate during the COVID-19 pandemic: case studies in the United States and the Philippines.

Uyheng, Joshua / Carley, Kathleen M

Journal of computational social science

2020 Volume 3, Issue 2, Page(s) 445–468

Abstract: Online hate speech represents a serious problem exacerbated by the ongoing COVID-19 pandemic. Although often anchored in real-world social divisions, hate speech in cyberspace may also be fueled inorganically by inauthentic actors like social bots. This ... ...

Abstract	Online hate speech represents a serious problem exacerbated by the ongoing COVID-19 pandemic. Although often anchored in real-world social divisions, hate speech in cyberspace may also be fueled inorganically by inauthentic actors like social bots. This work presents and employs a methodological pipeline for assessing the links between hate speech and bot-driven activity through the lens of social cybersecurity. Using a combination of machine learning and network science tools, we empirically characterize Twitter conversations about the pandemic in the United States and the Philippines. Our integrated analysis reveals idiosyncratic relationships between bots and hate speech across datasets, highlighting different network dynamics of racially charged toxicity in the US and political conflicts in the Philippines. Most crucially, we discover that bot activity is linked to higher hate in both countries, especially in communities which are denser and more isolated from others. We discuss several insights for probing issues of online hate speech and coordinated disinformation, especially through a global approach to computational social science.
Keywords	covid19
Language	English
Publishing date	2020-10-20
Publishing country	Singapore
Document type	Journal Article
ZDB-ID	2916161-7
ISSN	2432-2725 ; 2432-2717
ISSN (online)	2432-2725
ISSN	2432-2717
DOI	10.1007/s42001-020-00087-4
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

Order via subito

Details ▾
- Full text online
- Order with fees

Article: The Language of Pandemic Leaderships: Mapping Political Rhetoric During the COVID-19 Outbreak.

Montiel, Cristina Jayme / Uyheng, Joshua / Dela Paz, Erwine

Political psychology

2021 Volume 42, Issue 5, Page(s) 747–766

Abstract: This article maps political rhetoric by national leaders during the COVID-19 pandemic. We identify and characterize global variations in major rhetorical storylines invoked in publicly available speeches ( ...

Abstract	This article maps political rhetoric by national leaders during the COVID-19 pandemic. We identify and characterize global variations in major rhetorical storylines invoked in publicly available speeches (
Language	English
Publishing date	2021-04-23
Publishing country	United States
Document type	Journal Article
ZDB-ID	1500248-2
ISSN	1467-9221 ; 0162-895X
ISSN (online)	1467-9221
ISSN	0162-895X
DOI	10.1111/pops.12753
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

Order via subito

Details ▾
- Full text online
- Order with fees

Article: Active, aggressive, but to little avail: characterizing bot activity during the 2020 Singaporean elections.

Uyheng, Joshua / Ng, Lynnette Hui Xian / Carley, Kathleen M

Computational and mathematical organization theory

2021 Volume 27, Issue 3, Page(s) 324–342

Abstract: Digital disinformation presents a challenging problem for democracies worldwide, especially in times of crisis like the COVID-19 pandemic. In countries like Singapore, legislative efforts to quell fake news constitute relatively new and understudied ... ...

Abstract	Digital disinformation presents a challenging problem for democracies worldwide, especially in times of crisis like the COVID-19 pandemic. In countries like Singapore, legislative efforts to quell fake news constitute relatively new and understudied contexts for understanding local information operations. This paper presents a social cybersecurity analysis of the 2020 Singaporean elections, which took place at the height of the pandemic and after the recent passage of an anti-fake news law. Harnessing a dataset of 240,000 tweets about the elections, we found that 26.99% of participating accounts were likely to be bots, responsible for a larger proportion of bot tweets than the election in 2015. Textual analysis further showed that the detected bots used simpler and more abusive second-person language, as well as hashtags related to COVID-19 and voter activity-pointing to aggressive tactics potentially fuelling online hostility and questioning the legitimacy of the polls. Finally, bots were associated with larger, less dense, and less echo chamber-like communities, suggesting efforts to participate in larger, mainstream conversations. However, despite their distinct narrative and network maneuvers, bots generally did not hold significant influence throughout the social network. Hence, although intersecting concerns of political conflict during a global pandemic may promptly raise the possibility of online interference, we quantify both the efforts and limits of bot-fueled disinformation in the 2020 Singaporean elections. We conclude with several implications for digital disinformation in times of crisis, in the Asia-Pacific and beyond.
Language	English
Publishing date	2021-05-04
Publishing country	United States
Document type	Journal Article
ZDB-ID	2012211-1
ISSN	1572-9346 ; 1381-298X
ISSN (online)	1572-9346
ISSN	1381-298X
DOI	10.1007/s10588-021-09332-1
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

Order via subito

Details ▾
- Full text online
- Order with fees

Article ; Online: Mapping state-sponsored information operations with multi-view modularity clustering

Joshua Uyheng / Iain J. Cruickshank / Kathleen M. Carley

EPJ Data Science, Vol 11, Iss 1, Pp 1-

2022 Volume 29

Abstract: Abstract This paper presents a new computational framework for mapping state-sponsored information operations into distinct strategic units. Utilizing a novel method called multi-view modularity clustering (MVMC), we identify groups of accounts engaged ... ...

Abstract	Abstract This paper presents a new computational framework for mapping state-sponsored information operations into distinct strategic units. Utilizing a novel method called multi-view modularity clustering (MVMC), we identify groups of accounts engaged in distinct narrative and network information maneuvers. We then present an analytical pipeline to holistically determine their coordinated and complementary roles within the broader digital campaign. Applying our proposed methodology to disclosed Chinese state-sponsored accounts on Twitter, we discover an overarching operation to protect and manage Chinese international reputation by attacking individual adversaries (Guo Wengui) and collective threats (Hong Kong protestors), while also projecting national strength during global crisis (the COVID-19 pandemic). Psycholinguistic tools quantify variation in narrative maneuvers employing hateful and negative language against critics in contrast to communitarian and positive language to bolster national solidarity. Network analytics further distinguish how groups of accounts used network maneuvers to act as balanced operators, organized masqueraders, and egalitarian echo-chambers. Collectively, this work breaks methodological ground on the interdisciplinary application of unsupervised and multi-view methods for characterizing not just digital campaigns in particular, but also coordinated activity more generally. Moreover, our findings contribute substantive empirical insights around how state-sponsored information operations combine narrative and network maneuvers to achieve interlocking strategic objectives. This bears both theoretical and policy implications for platform regulation and understanding the evolving geopolitical significance of cyberspace.
Keywords	COVID-19 pandemic ; Information operations ; Multi-view modularity clustering ; State-sponsored disinformation ; Social cyber-security ; Unsupervised machine learning ; Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	006
Language	English
Publishing date	2022-04-01T00:00:00Z
Publisher	SpringerOpen
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article: Bots and online hate during the COVID-19 pandemic: case studies in the United States and the Philippines

Uyheng, Joshua / Carley, Kathleen M

J Comput Soc Sci

Abstract	Online hate speech represents a serious problem exacerbated by the ongoing COVID-19 pandemic. Although often anchored in real-world social divisions, hate speech in cyberspace may also be fueled inorganically by inauthentic actors like social bots. This work presents and employs a methodological pipeline for assessing the links between hate speech and bot-driven activity through the lens of social cybersecurity. Using a combination of machine learning and network science tools, we empirically characterize Twitter conversations about the pandemic in the United States and the Philippines. Our integrated analysis reveals idiosyncratic relationships between bots and hate speech across datasets, highlighting different network dynamics of racially charged toxicity in the US and political conflicts in the Philippines. Most crucially, we discover that bot activity is linked to higher hate in both countries, especially in communities which are denser and more isolated from others. We discuss several insights for probing issues of online hate speech and coordinated disinformation, especially through a global approach to computational social science.
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #888325
Database	COVID19

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾

Book ; Online: Affective Polarization in Online Climate Change Discourse on Twitter

Tyagi, Aman / Uyheng, Joshua / Carley, Kathleen M.

2020

Abstract: Online social media has become an important platform to organize around different socio-cultural and political topics. An extensive scholarship has discussed how people are divided into echo-chamber-like groups. However, there is a lack of work related ... ...

Abstract	Online social media has become an important platform to organize around different socio-cultural and political topics. An extensive scholarship has discussed how people are divided into echo-chamber-like groups. However, there is a lack of work related to quantifying hostile communication or \textit{affective polarization} between two competing groups. This paper proposes a systematic, network-based methodology for examining affective polarization in online conversations. Further, we apply our framework to 100 weeks of Twitter discourse about climate change. We find that deniers of climate change (Disbelievers) are more hostile towards people who believe (Believers) in the anthropogenic cause of climate change than vice versa. Moreover, Disbelievers use more words and hashtags related to natural disasters during more hostile weeks as compared to Believers. These findings bear implications for studying affective polarization in online discourse, especially concerning the subject of climate change. Lastly, we discuss our findings in the context of increasingly important climate change communication research.
Keywords	Computer Science - Social and Information Networks
Subject code	303
Publishing date	2020-08-29
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Impact of vaccine supplies and delays on optimal control of the COVID-19 pandemic: mapping interventions for the Philippines.

Estadilla, Carlo Delfin S / Uyheng, Joshua / de Lara-Tuprio, Elvira P / Teng, Timothy Robin / Macalalag, Jay Michael R / Estuar, Maria Regina Justina E

Infectious diseases of poverty

2021 Volume 10, Issue 1, Page(s) 107

Abstract: Background: Around the world, controlling the COVID-19 pandemic requires national coordination of multiple intervention strategies. As vaccinations are globally introduced into the repertoire of available interventions, it is important to consider how ... ...

Abstract	Background: Around the world, controlling the COVID-19 pandemic requires national coordination of multiple intervention strategies. As vaccinations are globally introduced into the repertoire of available interventions, it is important to consider how changes in the local supply of vaccines, including delays in administration, may be addressed through existing policy levers. This study aims to identify the optimal level of interventions for COVID-19 from 2021 to 2022 in the Philippines, which as a developing country is particularly vulnerable to shifting assumptions around vaccine availability. Furthermore, we explore optimal strategies in scenarios featuring delays in vaccine administration, expansions of vaccine supply, and limited combinations of interventions. Methods: Embedding our work within the local policy landscape, we apply optimal control theory to the compartmental model of COVID-19 used by the Philippine government's pandemic surveillance platform and introduce four controls: (a) precautionary measures like community quarantines, (b) detection of asymptomatic cases, (c) detection of symptomatic cases, and (d) vaccinations. The model is fitted to local data using an L-BFGS minimization procedure. Optimality conditions are identified using Pontryagin's minimum principle and numerically solved using the forward-backward sweep method. Results: Simulation results indicate that early and effective implementation of both precautionary measures and symptomatic case detection is vital for averting the most infections at an efficient cost, resulting in [Formula: see text] reduction of infections compared to the no-control scenario. Expanding vaccine administration capacity to 440,000 full immunizations daily will reduce the overall cost of optimal strategy by [Formula: see text], while allowing for a faster relaxation of more resource-intensive interventions. Furthermore, delays in vaccine administration require compensatory increases in the remaining policy levers to maintain a minimal number of infections. For example, delaying the vaccines by 180 days (6 months) will result in an [Formula: see text] increase in the cost of the optimal strategy. Conclusion: We conclude with practical insights regarding policy priorities particularly attuned to the Philippine context, but also applicable more broadly in similar resource-constrained settings. We emphasize three key takeaways of (a) sustaining efficient case detection, isolation, and treatment strategies; (b) expanding not only vaccine supply but also the capacity to administer them, and; (c) timeliness and consistency in adopting policy measures.
MeSH term(s)	Algorithms ; COVID-19/epidemiology ; COVID-19/mortality ; COVID-19/prevention & control ; COVID-19/transmission ; COVID-19 Vaccines/supply & distribution ; COVID-19 Vaccines/therapeutic use ; Developing Countries ; Humans ; Models, Statistical ; Philippines/epidemiology ; Population Surveillance
Chemical Substances	COVID-19 Vaccines
Language	English
Publishing date	2021-08-09
Publishing country	England
Document type	Journal Article
ZDB-ID	2689396-4
ISSN	2049-9957 ; 2049-9957
ISSN (online)	2049-9957
ISSN	2049-9957
DOI	10.1186/s40249-021-00886-5
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

To top

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

Full text online

More links

Kategorien

Order via subito

Full text online

More links

Kategorien

Order via subito

Full text online

More links

Kategorien

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

Order via subito