HCOct 30, 2020

Time-position characterization of conflicts: a case study of collaborative editing

arXiv:2010.16153v1
AI Analysis

This work addresses conflict prediction in collaborative editing for distributed teams, but it is incremental as it builds on existing session fragmentation methods.

The study tackled the problem of characterizing conflicts in collaborative editing by analyzing logs from 108 documents, finding that potential conflicts are rare but highly likely to become real conflicts.

Collaborative editing (CE) became increasingly common, often compulsory in academia and industry where people work in teams and are distributed across space and time. We aim to study collabora-tive editing behavior in terms of collaboration patterns users adopt and in terms of a characterisation of conflicts, i.e. edits from different users that occur close in time and position in the document. The process of a CE can be split into several editing 'sessions' which are performed by a single author ('single-authored session') or several authors ('co-authored session'). This fragmentation process requires a pre-defined 'maximum time gap' between sessions which is not yet well defined in previous studies. In this study, we analysed CE logs of 108 collaboratively edited documents. We show how to establish a suitable 'maximum time gap' to split CE activities into sessions by evaluating the distribution of the time distance between two adjacent sessions. We studied editing activities inside each 'co-author session' in order to define potential conflicts in terms of time and position dimensions before they occur in the document. We also analysed how many of these potential conflicts become real conflicts. Findings show that potential conflicting cases are few. However, they are more likely to become real conflicts.

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