Literature DB >> 32425212

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

Oduwa Edo-Osagie1, Beatriz De La Iglesia2, Iain Lake3, Obaghe Edeghere4.   

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.
Copyright © 2020. Published by Elsevier Ltd.

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

Year:  2020        PMID: 32425212      PMCID: PMC7229729          DOI: 10.1016/j.compbiomed.2020.103770

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  55 in total

1.  TOWARDS EARLY DISCOVERY OF SALIENT HEALTH THREATS: A SOCIAL MEDIA EMOTION CLASSIFICATION TECHNIQUE.

Authors:  Bahadorreza Ofoghi; Meghan Mann; Karin Verspoor
Journal:  Pac Symp Biocomput       Date:  2016

Review 2.  A systematic review of models for forecasting the number of emergency department visits.

Authors:  M Wargon; B Guidet; T D Hoang; G Hejblum
Journal:  Emerg Med J       Date:  2009-06       Impact factor: 2.740

3.  Evaluating social media's capacity to develop engaged audiences in health promotion settings: use of Twitter metrics as a case study.

Authors:  Brad L Neiger; Rosemary Thackeray; Scott H Burton; Christophe G Giraud-Carrier; Michael C Fagen
Journal:  Health Promot Pract       Date:  2012-12-27

4.  Semantic network analysis of vaccine sentiment in online social media.

Authors:  Gloria J Kang; Sinclair R Ewing-Nelson; Lauren Mackey; James T Schlitt; Achla Marathe; Kaja M Abbas; Samarth Swarup
Journal:  Vaccine       Date:  2017-05-27       Impact factor: 3.641

5.  Predicting asthma-related emergency department visits using big data.

Authors:  Sudha Ram; Wenli Zhang; Max Williams; Yolande Pengetnze
Journal:  IEEE J Biomed Health Inform       Date:  2015-02-19       Impact factor: 5.772

6.  SimNest: Social Media Nested Epidemic Simulation via Online Semi-supervised Deep Learning.

Authors:  Liang Zhao; Jiangzhuo Chen; Feng Chen; Wei Wang; Chang-Tien Lu; Naren Ramakrishnan
Journal:  Proc IEEE Int Conf Data Min       Date:  2015-11

7.  TEXT CLASSIFICATION FOR AUTOMATIC DETECTION OF E-CIGARETTE USE AND USE FOR SMOKING CESSATION FROM TWITTER: A FEASIBILITY PILOT.

Authors:  Yin Aphinyanaphongs; Armine Lulejian; Duncan Penfold Brown; Richard Bonneau; Paul Krebs
Journal:  Pac Symp Biocomput       Date:  2016

Review 8.  A scoping review of scoping reviews: advancing the approach and enhancing the consistency.

Authors:  Mai T Pham; Andrijana Rajić; Judy D Greig; Jan M Sargeant; Andrew Papadopoulos; Scott A McEwen
Journal:  Res Synth Methods       Date:  2014-07-24       Impact factor: 5.273

9.  Detection of illicit online sales of fentanyls via Twitter.

Authors:  Tim K Mackey; Janani Kalyanam
Journal:  F1000Res       Date:  2017-11-02

10.  DEFENDER: Detecting and Forecasting Epidemics Using Novel Data-Analytics for Enhanced Response.

Authors:  Nicholas Thapen; Donal Simmie; Chris Hankin; Joseph Gillard
Journal:  PLoS One       Date:  2016-05-18       Impact factor: 3.240

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