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

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

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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
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	https://doi.org/10.1109/HealthCom.2016.7749497
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
Nummer	18
Lokation	BMW Welt
Land/Område	Tyskland
By	Munich
Periode	14/09/2016 → 17/09/2016
Internetadresse	http://ieeehealthcom2016.com/

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Citationsformater

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. I A. Paulin (red.), 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom) (s. 442-447). Artikel 7749497 IEEE. https://doi.org/10.1109/HealthCom.2016.7749497

@inproceedings{4c9eab06140e4ac4824d1ce275deb574,

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",

year = "2016",

doi = "10.1109/HealthCom.2016.7749497",

language = "English",

pages = "442--447",

editor = "Alois Paulin",

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

publisher = "IEEE",

address = "United States",

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

url = "http://ieeehealthcom2016.com/",

}

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. i A Paulin (red.), 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)., 7749497, IEEE, Los Alamitos, CA, s. 442-447, IEEE HealthCom 16, Munich, Tyskland, 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). red. / Alois Paulin. Los Alamitos, CA: IEEE, 2016. s. 442-447 7749497.

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

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AU - Langberg, Henning

AU - Vatrapu, Ravi

N1 - Conference code: 18

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N2 - 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.

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.

U2 - 10.1109/HealthCom.2016.7749497

DO - 10.1109/HealthCom.2016.7749497

M3 - Article in proceedings

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

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