AIMC Topic: Social Media

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Deepfake detection by human crowds, machines, and machine-informed crowds.

Proceedings of the National Academy of Sciences of the United States of America Jan 4, 2022
The recent emergence of machine-manipulated media raises an important societal question: How can we know whether a video that we watch is real or fake? In two online studies with 15,016 participants, we present authentic videos and deepfakes and ask ...
Humans Artificial Intelligence Video Recording Forensic Sciences Facial Recognition Deception Social Media Communication
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Ontology-Based Natural Language Processing of Social Media Data in the Assessment of Health Information Sought During Pregnancy.

Studies in health technology and informatics Dec 15, 2021
This study analyzed collected social media data from South Korea containing keywords related to "pregnancy" using ontology-based natural language processing. Of the 504,725 documents, those containing concepts related to "maternal emotion" were the m...
Family Social Media Natural Language Processing Humans Pregnancy Female Republic of Korea
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DeepADEMiner: a deep learning pharmacovigilance pipeline for extraction and normalization of adverse drug event mentions on Twitter.

Journal of the American Medical Informatics Association : JAMIA Sep 18, 2021
OBJECTIVE: Research on pharmacovigilance from social media data has focused on mining adverse drug events (ADEs) using annotated datasets, with publications generally focusing on 1 of 3 tasks: ADE classification, named entity recognition for identify...
Pharmacovigilance Deep Learning Social Media Drug-Related Side Effects and Adverse Reactions Humans
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Drowning in the literature? These smart software tools can help.

Nature Sep 1, 2021
Periodicals as Topic Research Report Research Personnel Bibliometrics Social Media Knowledge Discovery Electronic Mail Preprints as Topic Search Engine Social Networking Artificial Intelligence Machine Learning Authorship Male Software Humans Academic Dissertations as Topic
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Food for thought: A natural language processing analysis of the 2020 Dietary Guidelines publice comments.

The American journal of clinical nutrition Aug 2, 2021
BACKGROUND: The Administrative Procedure Act of 1946 guarantees the public an opportunity to view and comment on the 2020 Dietary Guidelines as part of the policymaking process. In the past, public comments were submitted by postal mail or public hea...
Food Nutrition Policy Social Media Natural Language Processing Humans Diet
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Why do people oppose mask wearing? A comprehensive analysis of U.S. tweets during the COVID-19 pandemic.

Journal of the American Medical Informatics Association : JAMIA Jul 14, 2021
OBJECTIVE: Facial masks are an essential personal protective measure to fight the COVID-19 (coronavirus disease) pandemic. However, the mask adoption rate in the United States is still less than optimal. This study aims to understand the beliefs held...
Public Opinion Masks Social Media Attitude to Health Machine Learning COVID-19 United States Humans
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Developing a standardized protocol for computational sentiment analysis research using health-related social media data.

Journal of the American Medical Informatics Association : JAMIA Jun 12, 2021
OBJECTIVE: Sentiment analysis is a popular tool for analyzing health-related social media content. However, existing studies exhibit numerous methodological issues and inconsistencies with respect to research design and results reporting, which could...
Machine Learning Data Analysis Natural Language Processing Data Curation Social Media Humans Attitude to Health
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Identifying HIV-related digital social influencers using an iterative deep learning approach.

AIDS (London, England) May 1, 2021
OBJECTIVES: Community popular opinion leaders have played a critical role in HIV prevention interventions. However, it is often difficult to identify these 'HIV influencers' who are qualified and willing to promote HIV campaigns, especially online, b...
United States Social Media Deep Learning HIV Infections Humans
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The risk of racial bias while tracking influenza-related content on social media using machine learning.

Journal of the American Medical Informatics Association : JAMIA Mar 18, 2021
OBJECTIVE: Machine learning is used to understand and track influenza-related content on social media. Because these systems are used at scale, they have the potential to adversely impact the people they are built to help. In this study, we explore t...
Support Vector Machine Social Media Influenza, Human Neural Networks, Computer Machine Learning Black or African American Racism Influenza Vaccines Datasets as Topic Humans
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Emergency department frequent user subgroups: Development of an empirical, theory-grounded definition using population health data and machine learning.

Families, systems & health : the journal of collaborative family healthcare Mar 1, 2021
Frequent emergency department (ED) use has been operationalized in research, clinical practice, and policy as number of visits to the ED, despite the fact that this definition lacks empirical evidence and theoretical foundation. To date, there are no...
Patient Acceptance of Health Care Florida Population Health Management Grounded Theory Cluster Analysis Social Media Emergency Service, Hospital Humans Machine Learning
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