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

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Nadiya Straton, Kjeld Hansen, Raghava Rao Mukkamala, Abid Hussain, Tor Morten Grønli, Henning Langberg, 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.

Original languageEnglish
Title of host publication2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016
Number of pages6
PublisherIEEE
Publication date2016
Article number7749497
ISBN (Electronic)978-1-5090-3370-6
DOIs
Publication statusPublished - 2016
Event18th IEEE International Conference on e-Health Networking, Applications and Services, Healthcom 2016 - Munich, Germany
Duration: 14 Sep 201617 Sep 2016

Conference

Conference18th IEEE International Conference on e-Health Networking, Applications and Services, Healthcom 2016
LandGermany
ByMunich
Periode14/09/201617/09/2016

ID: 178884364