Abstract
Group discussions are usually aimed at sharing opinions, reaching consensus and making good decisions based on group knowledge. During a discussion, participants might adjust their own opinions as well as tune their attitudes towards others’ opinions, based on the unfolding interactions. In this paper, we demonstrate a framework to visualize such dynamics; at each instant of a conversation, the participants’ opinions and potential influence on their counterparts is easily visualized. We use multi-party meeting opinion mining based on bipartite graphs to extract opinions and calculate mutual influential factors, using the Lunar Survival Task as a study case.
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CITATION STYLE
Zhang, N., Zhang, T., Bhattacharya, I., Ji, H., & Radke, R. J. (2018). Visualizing group dynamics based on multiparty meeting understanding. In EMNLP 2018 - Conference on Empirical Methods in Natural Language Processing: System Demonstrations, Proceedings (pp. 96–101). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/d18-2017
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