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Different every time: A framework to model real-time instant message conversations
Dunne, Jonathan; Malone, David
As startups and micro teams adopt real-time collaborative instant messaging solutions, a wealth of data is generated from day to day usage. Making sense of this data can be a challenge to teams, given the lack of inbuilt analytical tooling. In this study we model the distributions of duration, inter-arrival time, word count and user count of real-time electronic chat conversations in a framework, where these distributions can be used as an analogue to service time estimation of problem determination. Using both an enterprise and an open-source dataset, we answer the question of what distribution family and fitting techniques can be used to adequately model real-time chat conversations. Our framework can help startups and micro teams alike to effectively model their real-time chat conversations to allow high value decisions to be made based on their collaboration outputs.
Keyword(s): Kernel; Real-time systems; Data models; Collaboration; Estimation; Bandwidth; Internet; electronic messaging; groupware; public domain software; real-time systems; real-time chat conversations; real-time collaborative instant messaging solutions; real-time electronic chat conversations; open-source dataset
Publication Date:
Type: Book chapter
Peer-Reviewed: Yes
Institution: Maynooth University
Citation(s): Dunne, Jonathan and Malone, David (2017) Different every time: A framework to model real-time instant message conversations. In: Proceedings of the 21st Conference of Open Innovations Association FRUCT. FRUCT, Oy, Finland, pp. 88-99. ISBN 978-952-68653-2-4
Publisher(s): FRUCT
File Format(s): other
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First Indexed: 2020-04-02 06:04:07 Last Updated: 2020-04-02 06:04:07