Big social data analytics for public health: Facebook engagement and performance

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

  • Nadiya Straton
  • Kjeld Hansen
  • Raghava Rao Mukkamala
  • Abid Hussain
  • Tor Morten Grønli
  • Langberg, Henning
  • Ravi Vatrapu

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.

OriginalsprogEngelsk
Titel2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016
Antal sider6
ForlagIEEE
Publikationsdato2016
Artikelnummer7749497
ISBN (Elektronisk)978-1-5090-3370-6
DOI
StatusUdgivet - 2016
Begivenhed18th IEEE International Conference on e-Health Networking, Applications and Services, Healthcom 2016 - Munich, Tyskland
Varighed: 14 sep. 201617 sep. 2016

Konference

Konference18th IEEE International Conference on e-Health Networking, Applications and Services, Healthcom 2016
LandTyskland
ByMunich
Periode14/09/201617/09/2016

ID: 178884364