Supporting industrial processes by monitoring and visualizing collaborations
Michele Biancucci, Jordan Janeiro, Massimo Mecella, Stephan G. Lukosch · 2014
In modern dynamic industrial engineering collaboration contexts, professionals such as the facilitators or meeting coordinators, are required to guide participants before, during and after a collaborative process in order to evaluate individual and group performances and the levels of idea generation, discussion, etc. This paper presents a collaboration support system, REGALMINER, that is able to capture, process, monitor and also visualize metadata from collaboration data streams taking advantage of text mining and information retrieval techniques like sentiment analysis (a.k.a. opinion mining) and keyword extraction. The analysis produces a set of scores that represent various meeting indicators that can be used to monitor and evaluate the dynamics of an ongoing collaborative process and to provide automatic interventions to enhance its effectiveness and efficiency. Information visualization techniques are used to present the results of the analysis to the participants of the current collaborative process or to the meeting coordinator, who supervises the meeting at runtime preventing the occurrence of deviations with respect to the meeting agenda and to make necessary interventions.