Social Collaboration Analytics for Enterprise Collaboration Systems: Providing Business Intelligence on Collaboration Activities

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dc.contributor.author Schwade, Florian
dc.contributor.author Schubert, Petra
dc.date.accessioned 2016-12-29T00:14:31Z
dc.date.available 2016-12-29T00:14:31Z
dc.date.issued 2017-01-04
dc.description.abstract The success of public Social Media has led to the emergence of Enterprise Social Software (ESS), a new type of collaboration software for organizations that incorporates “social features”. Surveys show that many companies are trying to implement ESS but that adoption is slower than expected. We believe that in order to understand the issues with its implementation we need to first examine and understand the “social” interactions that are taking place in this new kind of collaboration software. We propose Social Collaboration Analytics (SCA), a specialized form of examination of log files and content data, to gain a better understanding of the actual usage of ESS. Our research was guided by the CRISP-DM approach. We first analyzed the data available in a leading ESS. Together with leading user companies of this ESS, we then developed a framework for Social Collaboration Analysis, which we present in this paper.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2017.048
dc.identifier.isbn 978-0-9981331-0-2
dc.identifier.uri http://hdl.handle.net/10125/41197
dc.language.iso eng
dc.relation.ispartof Proceedings of the 50th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Social Collaboration Analytics
dc.subject Enterprise Collaboration Systems
dc.subject Enterprise Social Software
dc.subject Groupware
dc.subject Logfile Analysis
dc.title Social Collaboration Analytics for Enterprise Collaboration Systems: Providing Business Intelligence on Collaboration Activities
dc.type Conference Paper
dc.type.dcmi Text
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