Abstract
In recent years, social media has offered new opportunities
for interaction and distribution of public health
information within and across organisations. In this paper, we
analysed data from Facebook walls of 153 public organisations
using unsupervised machine learning techniques to understand
the characteristics of user engagement and post performance.
Our analysis indicates an increasing trend of user engagement on
public health posts during recent years. Based on the clustering
results, our analysis shows that Photo and Link type posts
are most favourable for high and medium user engagement
respectively.
Originalsprog | Engelsk |
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Titel | 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom) |
Redaktører | Alois Paulin |
Antal sider | 6 |
Udgivelsessted | Los Alamitos, CA |
Forlag | IEEE |
Publikationsdato | 2016 |
Sider | 442-447 |
Artikelnummer | 7749497 |
ISBN (Elektronisk) | 9781509033706, 9781509033713 |
DOI | |
Status | Udgivet - 2016 |
Begivenhed | IEEE HealthCom 16: 18th International Conference on E-health, Networking, Application & Services - BMW Welt, Munich, Tyskland Varighed: 14 sep. 2016 → 17 sep. 2016 Konferencens nummer: 18 http://ieeehealthcom2016.com/ |
Konference
Konference | IEEE HealthCom 16 |
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Nummer | 18 |
Lokation | BMW Welt |
Land/Område | Tyskland |
By | Munich |
Periode | 14/09/2016 → 17/09/2016 |
Internetadresse |