Predictive modeling and the ecology of hunter-gatherers of the boreal forest of Manitoba
In: BAR
In: International series 1221
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In: BAR
In: International series 1221
In: Open access government, Band 39, Heft 1, S. 152-153
ISSN: 2516-3817
Applying data science advances in disease surveillance and control
Dr. David S. Ebert and Dr. Aaron Wendelboe explain how a cohesive, multidisciplinary, and multi-tiered approach can support a more predictive model in disease surveillance and control. Public health disease surveillance is being conducted in countless settings, including healthcare, vertebrate and invertebrate animals, wastewater, air quality, transportation, and commercial activities, but, attaining the goal of early disease detection has been somewhat elusive. For instance, one of the few key shortcoming of public health preparedness efforts is the insufficient collaboration between multidisciplinary experts, such as data scientists, computer engineers, anthropologists, social scientists, and systems engineers. To address these gaps in knowledge and preparedness, we are responding in a multi-tiered approach with a One Health perspective that will be economically feasible and sustainable. The authors have also engaged a broad set of stakeholders, created broad multidisciplinary teams, are combining relevant data sources in innovative ways that will serve as early indicators, are using advanced technologies for early diagnosis, and advancing analytic methods to maintain high specificity for true event identification.
In: Journal of educational administration & history, Band 16, Heft 2, S. 45-53
ISSN: 1478-7431
In: Internet interventions: the application of information technology in mental and behavioural health ; official journal of the European Society for Research on Internet Interventions (ESRII) and the International Society for Research on Internet Interventions (ISRII), Band 28, S. 100457
ISSN: 2214-7829
SSRN
Working paper
In: Internet interventions: the application of information technology in mental and behavioural health ; official journal of the European Society for Research on Internet Interventions (ESRII) and the International Society for Research on Internet Interventions (ISRII), Band 5, S. 1-4
ISSN: 2214-7829
In: Neurotransmitter, Band 27, Heft 1, S. 48-57
ISSN: 2196-6397
In: Internet interventions: the application of information technology in mental and behavioural health ; official journal of the European Society for Research on Internet Interventions (ESRII) and the International Society for Research on Internet Interventions (ISRII), Band 17, S. 100245
ISSN: 2214-7829
In: Internet interventions: the application of information technology in mental and behavioural health ; official journal of the European Society for Research on Internet Interventions (ESRII) and the International Society for Research on Internet Interventions (ISRII), Band 12, S. 150-164
ISSN: 2214-7829
In: Internet interventions: the application of information technology in mental and behavioural health ; official journal of the European Society for Research on Internet Interventions (ESRII) and the International Society for Research on Internet Interventions (ISRII), Band 12, S. 165-175
ISSN: 2214-7829
In: American behavioral scientist: ABS, S. 000276422311743
ISSN: 1552-3381
Fake news about coronavirus disease 2019 (COVID-19) can discourage people from taking preventive measures (masks, social distancing), thereby increasing infections and deaths; thus, this study tests whether attributes of users or COVID-19 tweets can distinguish tweets of true news versus fake news. We analyzed 4,165 spell-checked English tweets with a link to 1 of 20 matched COVID-19 news stories (10 true and 10 fake), across the world during 1 year, via computational linguistics and advanced statistics. Tweets with common words, negative emotional valence, higher arousal, greater dominance, first person singular pronouns, third person pronouns or by users with more followers were more likely to be true news tweets. By contrast, tweets with second person pronouns, bald starts, or hedges were more likely to be fake news tweets. Accuracy (F1 score) was 95%. While some tweet attributes for detecting fake news might be universal (pronouns, politeness, followers), others might be topic specific (common words, emotions, hedges).
In: Internet interventions: the application of information technology in mental and behavioural health ; official journal of the European Society for Research on Internet Interventions (ESRII) and the International Society for Research on Internet Interventions (ISRII), Band 24, S. 100375
ISSN: 2214-7829
In: Internet interventions: the application of information technology in mental and behavioural health ; official journal of the European Society for Research on Internet Interventions (ESRII) and the International Society for Research on Internet Interventions (ISRII), Band 2, Heft 1, S. 7-16
ISSN: 2214-7829
In: Internet interventions: the application of information technology in mental and behavioural health ; official journal of the European Society for Research on Internet Interventions (ESRII) and the International Society for Research on Internet Interventions (ISRII), Band 26, S. 100455
ISSN: 2214-7829
In: Internet interventions: the application of information technology in mental and behavioural health ; official journal of the European Society for Research on Internet Interventions (ESRII) and the International Society for Research on Internet Interventions (ISRII), Band 19, S. 100296
ISSN: 2214-7829