Big Social Data Analytics for Public Health

Facebook Engagement and Performance

    Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review

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    Resumé

    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)
    RedaktørerAlois Paulin
    Antal sider6
    Udgivelses stedLos Alamitos, CA
    ForlagIEEE
    Publikationsdato2016
    Sider442-447
    Artikelnummer7749497
    ISBN (Elektronisk)9781509033706, 9781509033713
    DOI
    StatusUdgivet - 2016
    BegivenhedIEEE HealthCom 16: 18th International Conference on E-health, Networking, Application & Services - BMW Welt, Munich, Tyskland
    Varighed: 14 sep. 201617 sep. 2016
    Konferencens nummer: 18
    http://ieeehealthcom2016.com/

    Konference

    KonferenceIEEE HealthCom 16
    Nummer18
    LokationBMW Welt
    LandTyskland
    ByMunich
    Periode14/09/201617/09/2016
    Internetadresse

    Citer dette

    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). [7749497] Los Alamitos, CA: IEEE. https://doi.org/10.1109/HealthCom.2016.7749497
    Straton, Nadiya ; Hansen, Kjeld ; Mukkamala, Raghava Rao ; Hussain, Abid ; Grønli, Tor-Morten ; Langberg, Henning ; Vatrapu, Ravi. / Big Social Data Analytics for Public Health : Facebook Engagement and Performance. 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom). red. / Alois Paulin. Los Alamitos, CA : IEEE, 2016. s. 442-447
    @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",

    }

    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; Hussain, Abid; Grønli, Tor-Morten; Langberg, Henning; Vatrapu, Ravi.

    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/rapportKonferencebidrag i proceedingsForskningpeer review

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    AU - Grønli, Tor-Morten

    AU - Langberg, Henning

    AU - Vatrapu, Ravi

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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.

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    Straton N, Hansen K, Mukkamala RR, Hussain A, Grønli T-M, Langberg H et al. Big Social Data Analytics for Public Health: Facebook Engagement and Performance. I Paulin A, red., 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom). Los Alamitos, CA: IEEE. 2016. s. 442-447. 7749497 https://doi.org/10.1109/HealthCom.2016.7749497