How Social Media Will Change Public Health
Abstract
Recent work in machine learning and natural language processing has studied the health content of tweets and demonstrated the potential for extracting useful public health information from their aggregation. This article examines the types of health topics discussed on Twitter, and how tweets can both augment existing public health capabilities and enable new ones. The author also discusses key challenges that researchers must address to deliver high-quality tools to the public health community.
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Social media data, and Twitter posts in particular, are recorded in the moment and provide rich information about both the individual and the larger world.
“Because social media data (and Twitter posts in particular) are recorded in the moment, they provide rich information about both the individual as well as the larger world [30].”
From Psychosocial Effects of the COVID-19 Pandemic: Large-scale Quasi-Experimental Study on Social Media (2020) · cites this paper as [30]
Cites
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Earthquake shakes Twitter users
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From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series
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You Are What You Tweet: Analyzing Twitter for Public Health
Paul, M., & Dredze, M. H. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v5i1.14137 · Cited by 947 · see citing works
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Public Health Surveillance of Dental Pain via Twitter
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Social media, big data, and mental health: current advances and ethical implications
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“Extracting useful information from social media is not new, as the valuable geospatial insights from social media have been explored in a wide range of fields, including hazard mitigation [29–31], evacuation monitoring [27, 32, 33], urban analytics [34–37], and public health [38, 39], to list a few.”
BackgroundPsychosocial Effects of the COVID-19 Pandemic: Large-scale Quasi-Experimental Study on Social Media
Saha, K., Torous, J., Caine, E. D., & De Choudhury, M. (2020) · Journal of Medical Internet Research · doi:10.2196/22600 · Cited by 166 · see citing works
- Authors
- Dredze, M.
- Affiliations
- Johns Hopkins University (US)
- Corresponding author
- Dredze, Mark
- ORCID
- Dredze, Mark
- Venue
- IEEE Intelligent Systems
- Published
- 2012-07
- Volume
- 27
- Issue
- 4
- Pages
- 81-84
- ISSN
- 1541-1672 (ISSN-L)
- OpenAlex
- W1969894105
- Cited by
- 207
- References
- 9
- Citations by year
- 2025: 4 · 2024: 7 · 2023: 7 · 2022: 19 · 2021: 15 · 2020: 23 · 2019: 17 · 2018: 19 · 2017: 24 · 2016: 32 · 2015: 15 · 2014: 16 · 2013: 9
- FWCI
- 9.55
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Intelligent Systems (publishedVersion)
- Topics
- Health Sciences › Medicine › Epidemiology › Data-Driven Disease Surveillance
- Social Sciences › Health › Social Media in Health Education
- Social Sciences › Psychology › Social Psychology › Mental Health via Writing
- Keywords
- social media, public health, Twitter, tweets, health topics, natural language processing, machine learning, disease surveillance
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