Behavioral insights on big data: using social media for predicting biomedical outcomes. 2014

Sean D Young
Center for Digital Behavior, Department of Family Medicine, University of California, Los Angeles, CA, USA. Electronic address: youngsean@ucla.edu.

Social media 'big data' can provide valuable insights about people's behaviors, such as their likelihood of engaging in risk behaviors or contracting a disease. Although in its infancy, advancing this research provides the promise of predicting health-related behaviors to promptly prepare for and respond to public health emergencies and epidemics.

UI MeSH Term Description Entries
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D001525 Behavioral Sciences Disciplines concerned with the study of human and animal behavior. Proxemics,Behavioral Science,Proxemic,Science, Behavioral,Sciences, Behavioral
D061108 Social Media Platforms that provide the ability and tools to create and publish information accessed via the INTERNET. Generally these platforms have three characteristics with content user generated, high degree of interaction between creator and viewer, and easily integrated with other sites. Folksonomy,Mobile Social Media,Mobile Social Networks,Social Media Messaging,Social Tagging,Social Medium,Twitter Messaging,Web 2.0,Folksonomies,Media Messaging, Social,Media, Social,Messaging, Social Media,Messaging, Twitter,Mobile Social Medias,Mobile Social Network,Social Media Messagings,Social Media, Mobile,Social Network, Mobile,Social Taggings,Tagging, Social,Web 2.0s
D062665 Epidemiological Monitoring Collection, analysis, and interpretation of data about the frequency, distribution, and consequences of disease or health conditions, for use in the planning, implementing, and evaluating public health programs. Epidemiologic Monitoring,Epidemiologic Surveillance,Monitoring, Epidemiologic,Epidemiologic Surveillances,Monitoring, Epidemiological,Surveillance, Epidemiologic,Surveillances, Epidemiologic

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