[New Publication] Towards using agent-based modelling for collaborative translation of crisis information: A systematic literature review to identify the underlying attributes, behaviours, interactions, and environment of agents

https://www.sciencedirect.com/science/article/pii/S2212420921006786?dgcid=coauthor

By R.I.Ogie, S.O’Brien, F.M.Federici

Abstract

Collaboration in language translation has a long history and continues to develop in the form of crowdsourced and community translation. More recently, efforts in collaborative translation for crisis communication have been noted. These efforts are far from being mature in nature. We propose that Agent Based Modelling (ABM) for crisis translation could have significant benefits for the field of disaster response. A systematic literature review reveals how little consideration has been given to the topic to date. We review the limited literature from the perspective of agent’s attributes, behaviours, interactions, and their environmental and operational factors. These are useful as a list of observations to be considered in the future modelling of collaborative translation. The complexities of ABM for collaborative translation are also highlighted and we propose some theoretical underpinnings that could be used to further enhance ABM for collaborative crisis translation. Based on the new knowledge generated to support accurate modelling of collaborative translation, we conclude that ABM may offer an opportunity to verify if, and how, translation crowdsourcing can be best optimised to support multilingual communication across the different phases of a disaster or crisis lifecycle. ABM could offer opportunities to assess rules, attitudes, behaviours, and interactions of multiple actors, from professionals to bilingual volunteers in rare, non-commercial language combinations, with the view of identifying positive rewarding mechanisms, including both financial incentives and the opportunity to broaden one’s translation experience.

Keywords

Translation; Disaster; Crowdsourcing; Collaborative; Agent-based modelling; ABM
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