Metrics for Analyzing Social Documents to Understand Joint Work

Loading...
Thumbnail Image

Contributor

Advisor

Editor

Performer

Department

Instructor

Depositor

Speaker

Researcher

Consultant

Interviewer

Interviewee

Narrator

Transcriber

Annotator

Journal Title

Journal ISSN

Volume Title

Publisher

Journal Name

Volume

Number/Issue

Starting Page

Ending Page

Alternative Title

Abstract

Social Collaboration Analytics (SCA) aims at measuring and interpreting communication and joint work on collaboration platforms and is a relatively new topic in the discipline of Information Systems. Previous applications of SCA are largely based on transactional data (event logs). In this paper, we propose a novel approach for the examination of collaboration based on the structure of social documents. Guided by the ontology for social business documents (SocDOnt) we develop metrics to measure collaboration around documents that provide traces of collaborative activity. For the evaluation, we apply these metrics to a large-scale collaboration platform. The findings show that group workspaces that support the same use case are characterized by a similar richness of their social documents (i.e. the number of components and contributing authors). We also show typical differences in the “collaborativity” of functional modules (containers).

Description

Citation

Extent

10 pages

Format

Type

Conference Paper

Geographic Location

Time Period

Related To

Proceedings of the 53rd Hawaii International Conference on System Sciences

Related To (URI)

Table of Contents

Rights

Attribution-NonCommercial-NoDerivatives 4.0 International

Rights Holder

Catalog Record

Local Contexts

Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.