Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Jul:122:103770.
doi: 10.1016/j.compbiomed.2020.103770. Epub 2020 May 16.

A scoping review of the use of Twitter for public health research

Oduwa Edo-Osagie  1 , Beatriz De La Iglesia  2 , Iain Lake  3 , Obaghe Edeghere  4
Affiliations

A scoping review of the use of Twitter for public health research

Oduwa Edo-Osagie et al. Comput Biol Med. 2020 Jul.

Abstract

Public health practitioners and researchers have used traditional medical databases to study and understand public health for a long time. Recently, social media data, particularly Twitter, has seen some use for public health purposes. Every large technological development in history has had an impact on the behaviour of society. The advent of the internet and social media is no different. Social media creates public streams of communication, and scientists are starting to understand that such data can provide some level of access into the people's opinions and situations. As such, this paper aims to review and synthesize the literature on Twitter applications for public health, highlighting current research and products in practice. A scoping review methodology was employed and four leading health, computer science and cross-disciplinary databases were searched. A total of 755 articles were retreived, 92 of which met the criteria for review. From the reviewed literature, six domains for the application of Twitter to public health were identified: (i) Surveillance; (ii) Event Detection; (iii) Pharmacovigilance; (iv) Forecasting; (v) Disease Tracking; and (vi) Geographic Identification. From our review, we were able to obtain a clear picture of the use of Twitter for public health. We gained insights into interesting observations such as how the popularity of different domains changed with time, the diseases and conditions studied and the different approaches to understanding each disease, which algorithms and techniques were popular with each domain, and more.

Keywords: Disease tracking; Event forecasting; Pharmacovigilance; Public health; Syndromic surveillance.

PubMed Disclaimer

Conflict of interest statement

Declaration of competing interest None Declared.

Figures

Fig. 1
Fig. 1
PRISMA flow diagram for the identification and selection of studies.
Fig. 2
Fig. 2
Word cloud of statistical and machine learning methods discovered in review.
Fig. 3
Fig. 3
Breakdown of studies by country.
Fig. 4
Fig. 4
Most studied diseases each year. Generic feelings of unwellness and non-specific illness.
Fig. 5
Fig. 5
Most applied algorithms each year.
Fig. 6
Fig. 6
Bubble chart showing the trends of research activity in public health application domains with time. The size of the bubble represents the number of articles in each category and year.
Fig. 7
Fig. 7
Most applied algorithms each year.
See this image and copyright information in PMC

References

    1. World Health Organisation Who The world health report 2007 - a safer future: global public health security in the 21st century. 2007. http://www.who.int/whr/2007/en/
    1. Triple S. Assessment of syndromic surveillance in europe. Lancet. 2011;378(9806):1833. - PubMed
    1. Winslow C.-E. The untilled fields of public health. Science. 1920:23–33. - PubMed
    1. Neiger B.L., Thackeray R., Burton S.H., Giraud-Carrier C.G., Fagen M.C. Evaluating social media's capacity to develop engaged audiences in health promotion settings: use of twitter metrics as a case study. Health Promot. Pract. 2013;14(2):157–162. - PubMed
    1. Wargon M., Guidet B., Hoang T., Hejblum G. A systematic review of models for forecasting the number of emergency department visits. Emerg. Med. J. 2009;26(6):395–399. - PubMed

Publication types