Big Social Data Analytics for Public Health: Facebook Engagement and Performance

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

doi:10.1109/HealthCom.2016.7749497

Big Social Data Analytics for Public Health: Facebook Engagement and Performance

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

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

In recent years, social media has offered new opportunitiesfor interaction and distribution of public healthinformation within and across organisations. In this paper, weanalysed data from Facebook walls of 153 public organisationsusing unsupervised machine learning techniques to understandthe characteristics of user engagement and post performance.Our analysis indicates an increasing trend of user engagement onpublic health posts during recent years. Based on the clusteringresults, our analysis shows that Photo and Link type postsare most favourable for high and medium user engagementrespectively.

Original language	English
Title of host publication	2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)
Editors	Alois Paulin
Number of pages	6
Place of Publication	Los Alamitos, CA
Publisher	IEEE
Publication date	2016
Pages	442-447
Article number	7749497
ISBN (Electronic)	9781509033706, 9781509033713
DOIs	https://doi.org/10.1109/HealthCom.2016.7749497
Publication status	Published - 2016
Event	IEEE HealthCom 16: 18th International Conference on E-health, Networking, Application & Services - BMW Welt, Munich, Germany Duration: 14 Sept 2016 → 17 Sept 2016 Conference number: 18 http://ieeehealthcom2016.com/

Conference

Conference	IEEE HealthCom 16
Number	18
Location	BMW Welt
Country/Territory	Germany
City	Munich
Period	14/09/2016 → 17/09/2016
Internet address	http://ieeehealthcom2016.com/

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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Cite this

Straton, N., Hansen, K., Mukkamala, R. R., Hussain, A., Grønli, T.-M., Langberg, H., & Vatrapu, R. (2016). Big Social Data Analytics for Public Health: Facebook Engagement and Performance. In A. Paulin (Ed.), 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom) (pp. 442-447). Article 7749497 IEEE. https://doi.org/10.1109/HealthCom.2016.7749497

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title = "Big Social Data Analytics for Public Health: Facebook Engagement and Performance",

abstract = "In recent years, social media has offered new opportunitiesfor interaction and distribution of public healthinformation within and across organisations. In this paper, weanalysed data from Facebook walls of 153 public organisationsusing unsupervised machine learning techniques to understandthe characteristics of user engagement and post performance.Our analysis indicates an increasing trend of user engagement onpublic health posts during recent years. Based on the clusteringresults, our analysis shows that Photo and Link type postsare most favourable for high and medium user engagementrespectively.",

author = "Nadiya Straton and Kjeld Hansen and Mukkamala, {Raghava Rao} and Abid Hussain and Tor-Morten Gr{\o}nli and Henning Langberg and Ravi Vatrapu",

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doi = "10.1109/HealthCom.2016.7749497",

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editor = "Alois Paulin",

booktitle = "2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)",

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note = "IEEE HealthCom 16 ; Conference date: 14-09-2016 Through 17-09-2016",

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Straton, N, Hansen, K, Mukkamala, RR , Hussain, A, Grønli, T-M, Langberg, H & Vatrapu, R 2016, Big Social Data Analytics for Public Health: Facebook Engagement and Performance. in A Paulin (ed.), 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)., 7749497, IEEE, Los Alamitos, CA, pp. 442-447, IEEE HealthCom 16, Munich, Germany, 14/09/2016. https://doi.org/10.1109/HealthCom.2016.7749497

Big Social Data Analytics for Public Health: Facebook Engagement and Performance. / Straton, Nadiya; Hansen, Kjeld; Mukkamala, Raghava Rao et al.
2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom). ed. / Alois Paulin. Los Alamitos, CA: IEEE, 2016. p. 442-447 7749497.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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AB - In recent years, social media has offered new opportunitiesfor interaction and distribution of public healthinformation within and across organisations. In this paper, weanalysed data from Facebook walls of 153 public organisationsusing unsupervised machine learning techniques to understandthe characteristics of user engagement and post performance.Our analysis indicates an increasing trend of user engagement onpublic health posts during recent years. Based on the clusteringresults, our analysis shows that Photo and Link type postsare most favourable for high and medium user engagementrespectively.

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