Social Media-Based Expertise Evidence

Simple item page
dc.contributor.authorYogev, Arnon
dc.contributor.authorGuy, Ido
dc.contributor.authorRonen, Inbal
dc.contributor.authorZwerdling, Naama
dc.contributor.authorBarnea, Maya
dc.date.accessioned2017-10-23T11:55:28Z
dc.date.available2017-10-23T11:55:28Z
dc.date.issued2015
dc.description.abstractSocial media provides a fertile ground for expertise location. The public nature of the data supports expertise inference with little privacy infringement and, in addition, presentation of direct and detailed evidence for an expert’s skillfulness in the queried topic. In this work, we study the use of social media for expertise evidence. We conducted two user surveys of enterprise social media users within a large global organization, in which participants were asked to rate anonymous experts based on artificial and real evidence originating from different types of social media data. Our results indicate that the social media data types perceived most convincing as evidence are not necessarily the ones from which expertise can be inferred most precisely or effectively. We describe these results in detail and discuss implications for designers and architects of expertise location systems.en
dc.identifier.doi10.1007/978-3-319-20499-4_4
dc.identifier.isbn978-3-319-20498-7
dc.language.isoen
dc.publisherSpringer, Cham
dc.relation.ispartofECSCW 2015: Proceedings of the 14th European Conference on Computer Supported Cooperative Work
dc.relation.ispartofseriesECSCW
dc.titleSocial Media-Based Expertise Evidenceen
dc.typeText/Conference Paper
gi.citation.endPage82
gi.citation.startPage63
gi.conference.date19-23 September 2015
gi.conference.locationOslo, Norway
gi.conference.sessiontitleFull Papers

Files

Original bundle
1 - 1 of 1
Thumbnail Image
Name:
7 YogevGuyRonenZwerdlingBarnea2015.pdf
Size:
897.56 KB
Format:
Adobe Portable Document Format
Download

Collections

ECSCW 2015: Proceedings of the 14th European Conference on Computer Supported Cooperative Work