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Editorial

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Infoveillance and Social Listening

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Using infodemiology data for surveillance purposes has been called “infoveillance” [Eysenbach 2008, Eysenbach 2009]:

"Infoveillance is important for both the supply and demand sides. Public health professionals want to know, for example, if there is a surge of misinformation on the Internet on vaccination, so that public health campaigns and “health marketing” efforts can effectively counterbalance the misinformation. Public health professionals also need to know about surges in information demand, be it to address “epidemics of fear” by supplying the public with appropriate information, or to detect real disease outbreaks for which spikes in Internet searches or chatter in newsgroups and postings on microblogs (Twitter etc) may be an early predictor." [Eysenbach 2009]

The term "social listening" is sometimes used as a synonym for infoveillance, but has also been more narrowly defined as "the process of identifying and assessing what is being said about a company, product, brand, or individual, within forms of electronic interactive media" [Anderson et al, 2017]. The term "social listening" was first used in the public health context in 2015 by Heather Cole-Lewis when tracking sentiments on e-cigarettes on Twitter [Cole-Lewis et al, 2015].  

Infoveillance/social listening has been identified as one of the pillars to fight an infodemic [Tangcharoensathien et al, 2020; Eysenbach 2020].

See also related E-Collections: 

Infoveillance, Infodemiology and Digital Disease Surveillance  (JPHS)

Infodemiology and Infoveillance  (JMIR)



Infodemic Management

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Assessing and Building eHealth / Digital Literacy in Populations

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Training for Infodemic Managers and Public Health Professionals

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Misinformation and Disinformation Outbreaks and Information Prevalence Studies

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Information prevalence studies measure the absolute or relative number of occurrences of a certain keyword or concept (eg, misinformation or facts) in a pool of information [Eysenbach 2009]. These kinds of studies are particularly useful if we track them longitudinally (ie, track how the number of internet postings on a given health-specific topic changes over time), as we would, for example, to see changes in relation to certain external events, such as a media campaign or a disease outbreak.



Information Demand

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With demand-based infodemiology indicators we usually refer to data generated from the search and “click” (ie, navigation) behavior of people. [Eysenbach 2009]



Health and Risk Communication

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Policy for Infodemiology and Infodemic Management

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Equity Issues in Information Distribution

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Vaccination Sentiment and Anti-Vaccination Infodemiology

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Data Sources and Open Data for Infodemiology

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Bots and AI Approaches to Detect and Counter Misinformation

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Corrigenda and Addenda

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Discretionary Corrigenda

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