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  1. Article ; Online: Twitter social mobility data reveal demographic variations in social distancing practices during the COVID-19 pandemic.

    Xu, Paiheng / Broniatowski, David A / Dredze, Mark

    Scientific reports

    2024  Volume 14, Issue 1, Page(s) 1165

    Abstract: The COVID-19 pandemic demonstrated the importance of social distancing practices to stem the spread of the virus. However, compliance with public health guidelines was mixed. Understanding what factors are associated with differences in compliance can ... ...

    Abstract The COVID-19 pandemic demonstrated the importance of social distancing practices to stem the spread of the virus. However, compliance with public health guidelines was mixed. Understanding what factors are associated with differences in compliance can improve public health messaging since messages could be targeted and tailored to different population segments. We utilize Twitter data on social mobility during COVID-19 to reveal which populations practiced social distancing and what factors correlated with this practice. We analyze correlations between demographic and political affiliation with reductions in physical mobility measured by public geolocation tweets. We find significant differences in mobility reduction between these groups in the United States. We observe that males, Asian and Latinx individuals, older individuals, Democrats, and people from higher population density states exhibited larger reductions in movement. Furthermore, our study also unveils meaningful insights into the interactions between different groups. We hope these findings will provide evidence to support public health policy-making.
    MeSH term(s) Male ; Humans ; United States/epidemiology ; COVID-19/epidemiology ; COVID-19/prevention & control ; Physical Distancing ; SARS-CoV-2 ; Pandemics/prevention & control ; Social Media ; Social Mobility ; Demography
    Language English
    Publishing date 2024-01-12
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-024-51555-0
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Economic risk framing increases intention to vaccinate among Republican COVID-19 vaccine refusers.

    Zhong, Wei / Broniatowski, David A

    Social science & medicine (1982)

    2022  Volume 317, Page(s) 115594

    Abstract: Objective: To determine if framing communications about COVID-19 vaccines in economic terms can increase Republicans' likelihood to get vaccinated.: Methods: We examined Twitter posts between January 2020 and September 2021 by Democratic and ... ...

    Abstract Objective: To determine if framing communications about COVID-19 vaccines in economic terms can increase Republicans' likelihood to get vaccinated.
    Methods: We examined Twitter posts between January 2020 and September 2021 by Democratic and Republican politicians to determine how they framed the COVID-19 pandemic. Based on these posts, we carried out a survey study between September and November 2021 to examine whether motivations for COVID-19 vaccine uptake matched message frames that were widely used by these politicians. Finally, we conducted a randomized controlled experiment to examine how these frames (economic vs. health) affected intentions to vaccinate by vaccine refusers in both parties.
    Results: Republican politicians were more likely to frame the pandemic in economic terms, whereas Democrats predominantly used health frames. Accordingly, vaccinated Republicans' choices were more likely to be motivated by economic consideration (β = 0.25, p = 0.02) and personal financial rationales (β = 0.24, p = 0.03). Among vaccine refusers, Republicans exposed to messages using economic rationales to encourage vaccination reported higher vaccination intentions compared to those exposed to messages using public health rationales (F
    Conclusion: Messages highlighting economic and personal financial risks could increase intentions to vaccinate for vaccine-hesitant Republicans.
    Public health implications: Agencies should invest in developing messages that are congruent with frames that are already widely used by co-partisans. Social media may be helpful in eliciting these frames.
    MeSH term(s) Humans ; COVID-19/prevention & control ; COVID-19 Vaccines/therapeutic use ; Intention ; Pandemics ; Vaccination
    Chemical Substances COVID-19 Vaccines
    Language English
    Publishing date 2022-12-07
    Publishing country England
    Document type Journal Article ; Randomized Controlled Trial ; Research Support, Non-U.S. Gov't
    ZDB-ID 4766-1
    ISSN 1873-5347 ; 0037-7856 ; 0277-9536
    ISSN (online) 1873-5347
    ISSN 0037-7856 ; 0277-9536
    DOI 10.1016/j.socscimed.2022.115594
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    Zs.A 625: Show issues Location:
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    Jg. 1995 - 2021: Lesesall (1.OG)
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  3. Article ; Online: Inductive detection of influence operations via graph learning.

    Gabriel, Nicholas A / Broniatowski, David A / Johnson, Neil F

    Scientific reports

    2023  Volume 13, Issue 1, Page(s) 22571

    Abstract: Influence operations are large-scale efforts to manipulate public opinion. The rapid detection and disruption of these operations is critical for healthy public discourse. Emergent AI technologies may enable novel operations that evade detection and ... ...

    Abstract Influence operations are large-scale efforts to manipulate public opinion. The rapid detection and disruption of these operations is critical for healthy public discourse. Emergent AI technologies may enable novel operations that evade detection and influence public discourse on social media with greater scale, reach, and specificity. New methods of detection with inductive learning capacity will be needed to identify novel operations before they indelibly alter public opinion and events. To this end, we develop an inductive learning framework that: (1) determines content- and graph-based indicators that are not specific to any operation; (2) uses graph learning to encode abstract signatures of coordinated manipulation; and (3) evaluates generalization capacity by training and testing models across operations originating from Russia, China, and Iran. We find that this framework enables strong cross-operation generalization while also revealing salient indicators-illustrating a generic approach which directly complements transductive methodologies, thereby enhancing detection coverage.
    Language English
    Publishing date 2023-12-19
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-023-49676-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Volatility of vaccine confidence.

    Larson, Heidi J / Broniatowski, David A

    Science (New York, N.Y.)

    2021  Volume 371, Issue 6536, Page(s) 1289

    MeSH term(s) Anti-Vaccination Movement ; COVID-19/prevention & control ; COVID-19 Vaccines/adverse effects ; Health Communication ; Health Knowledge, Attitudes, Practice ; Humans ; Patient Acceptance of Health Care ; Vaccination ; Vaccination Refusal
    Chemical Substances COVID-19 Vaccines
    Language English
    Publishing date 2021-03-22
    Publishing country United States
    Document type Editorial
    ZDB-ID 128410-1
    ISSN 1095-9203 ; 0036-8075
    ISSN (online) 1095-9203
    ISSN 0036-8075
    DOI 10.1126/science.abi6488
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    Zs.A 27: Show issues Location:
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    Jg. 1995 - 2021: Lesesall (1.OG)
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  5. Article ; Online: Why Debunking Misinformation Is Not Enough to Change People's Minds About Vaccines.

    Larson, Heidi J / Broniatowski, David A

    American journal of public health

    2021  Volume 111, Issue 6, Page(s) 1058–1060

    MeSH term(s) COVID-19 Vaccines ; Communication ; Humans ; Trust ; Vaccination Refusal
    Chemical Substances COVID-19 Vaccines
    Language English
    Publishing date 2021-05-13
    Publishing country United States
    Document type Editorial ; Research Support, Non-U.S. Gov't
    ZDB-ID 121100-6
    ISSN 1541-0048 ; 0090-0036 ; 0002-9572
    ISSN (online) 1541-0048
    ISSN 0090-0036 ; 0002-9572
    DOI 10.2105/AJPH.2021.306293
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    Un I Zs.279: Show issues Location:
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    ab Jg. 2022: Lesesaal (EG)

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  6. Article: Do design decisions depend on "dictators"?

    Broniatowski, David A

    Research in engineering design

    2017  Volume 29, Issue 1, Page(s) 67–85

    Abstract: Design decisions often require input from multiple stakeholders or require balancing multiple design requirements. However, leading axiomatic approaches to decision-based design suggest that combining preferences across these elements is virtually ... ...

    Abstract Design decisions often require input from multiple stakeholders or require balancing multiple design requirements. However, leading axiomatic approaches to decision-based design suggest that combining preferences across these elements is virtually guaranteed to result in irrational outcomes. This has led some to conclude that a single "dictator" is required to make design decisions. In contrast, proponents of heuristic approaches observe that aggregate decisions are frequently made in practice, and argue that this widespread usage justifies the value of these heuristics to the engineering design community. This paper demonstrates that these approaches need not be mutually exclusive. Axiomatic approaches can be informed by empirically motivated restrictions on the way that individuals can order their preferences. These restrictions are represented using "anigrafs"-structured relationships between alternatives that are represented using a graph-theoretic formalism. This formalism allows for a computational assessment of the likelihood of irrational outcomes. Simulation results show that even minimal amounts of structure can vastly reduce the likelihood of irrational outcomes at the level of the group, and that slightly stronger restrictions yield probabilities of irrational preferences that never exceed 5%. Next, an empirical case study demonstrates how anigrafs may be extracted from survey data, and a model selection technique is introduced to examine the goodness-of-fit of these anigrafs to preference data. Taken together, these results show how axiomatic consistency can be combined with empirical correspondence to determine the circumstances under which "dictators" are necessary in design decisions.
    Language English
    Publishing date 2017-05-16
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1480792-0
    ISSN 1435-6066 ; 0934-9839
    ISSN (online) 1435-6066
    ISSN 0934-9839
    DOI 10.1007/s00163-017-0259-2
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  7. Article ; Online: Gist Representations and Decision-Making Processes Affecting Antibiotic Prescribing for Children with Acute Otitis Media.

    Marti, Deniz / Hamdy, Rana F / Broniatowski, David A

    MDM policy & practice

    2022  Volume 7, Issue 2, Page(s) 23814683221115416

    Abstract: Objective.: Highlights: We found clinicians' antibiotic prescription decisions were driven by gist representations of antibiotic risks for a given hypothetical patient scenario, and clinicians' gist representations and verbatim risk estimates about ... ...

    Abstract Objective.
    Highlights: We found clinicians' antibiotic prescription decisions were driven by gist representations of antibiotic risks for a given hypothetical patient scenario, and clinicians' gist representations and verbatim risk estimates about antibiotic-related risks were distinct from each other.We showed that the effect of patient scenarios on clinicians' antibiotic prescription decisions was mediated by clinicians' gist representations.Less experienced clinicians tend to "hedge" in their antibiotic prescription decisions compared with more experienced clinicians.The broader impact of our study is that antibiotic stewardship programs can benefit by communicating the appropriate gists to clinicians who prescribe antibiotics for pediatric patients, rather than solely focusing on closing potential knowledge deficits of the clinicians.
    Language English
    Publishing date 2022-07-26
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2861432-X
    ISSN 2381-4683 ; 2381-4683
    ISSN (online) 2381-4683
    ISSN 2381-4683
    DOI 10.1177/23814683221115416
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  8. Article ; Online: Abstraction: An alternative neurocognitive account of recognition, prediction, and decision making-ADDENDUM.

    Reyna, Valerie F / Broniatowski, David A

    The Behavioral and brain sciences

    2020  Volume 43, Page(s) e184

    Language English
    Publishing date 2020-12-02
    Publishing country England
    Document type Journal Article ; Published Erratum
    ZDB-ID 423721-3
    ISSN 1469-1825 ; 0140-525X
    ISSN (online) 1469-1825
    ISSN 0140-525X
    DOI 10.1017/S0140525X20000655
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1470: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  9. Article ; Online: Abstraction: An alternative neurocognitive account of recognition, prediction, and decision making.

    Reyna, Valerie F / Broniatowski, David A

    The Behavioral and brain sciences

    2020  Volume 43, Page(s) e144

    Abstract: Gilead et al. offer a thoughtful and much-needed treatment of abstraction. However, it fails to build on an extensive literature on abstraction, representational diversity, neurocognition, and psychopathology that provides important constraints and ... ...

    Abstract Gilead et al. offer a thoughtful and much-needed treatment of abstraction. However, it fails to build on an extensive literature on abstraction, representational diversity, neurocognition, and psychopathology that provides important constraints and alternative evidence-based conceptions. We draw on conceptions in software engineering, socio-technical systems engineering, and a neurocognitive theory with abstract representations of gist at its core, fuzzy-trace theory.
    MeSH term(s) Brain ; Decision Making
    Language English
    Publishing date 2020-06-19
    Publishing country England
    Document type Journal Article ; Comment
    ZDB-ID 423721-3
    ISSN 1469-1825 ; 0140-525X
    ISSN (online) 1469-1825
    ISSN 0140-525X
    DOI 10.1017/S0140525X19003017
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1470: 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)

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  10. Book ; Online: Inductive detection of Influence Operations via Graph Learning

    Gabriel, Nicholas A. / Broniatowski, David A. / Johnson, Neil F.

    2023  

    Abstract: Influence operations are large-scale efforts to manipulate public opinion. The rapid detection and disruption of these operations is critical for healthy public discourse. Emergent AI technologies may enable novel operations which evade current detection ...

    Abstract Influence operations are large-scale efforts to manipulate public opinion. The rapid detection and disruption of these operations is critical for healthy public discourse. Emergent AI technologies may enable novel operations which evade current detection methods and influence public discourse on social media with greater scale, reach, and specificity. New methods with inductive learning capacity will be needed to identify these novel operations before they indelibly alter public opinion and events. We develop an inductive learning framework which: 1) determines content- and graph-based indicators that are not specific to any operation; 2) uses graph learning to encode abstract signatures of coordinated manipulation; and 3) evaluates generalization capacity by training and testing models across operations originating from Russia, China, and Iran. We find that this framework enables strong cross-operation generalization while also revealing salient indicators$\unicode{x2013}$illustrating a generic approach which directly complements transductive methodologies, thereby enhancing detection coverage.
    Keywords Computer Science - Machine Learning ; Computer Science - Cryptography and Security ; Computer Science - Social and Information Networks ; Physics - Physics and Society
    Subject code 006
    Publishing date 2023-05-25
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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