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    <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.</abstract>
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%0 Conference Proceedings
%T Visualizing Group Dynamics based on Multiparty Meeting Understanding
%A Zhang, Ni
%A Zhang, Tongtao
%A Bhattacharya, Indrani
%A Ji, Heng
%A Radke, Rich
%Y Blanco, Eduardo
%Y Lu, Wei
%S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
%D 2018
%8 November
%I Association for Computational Linguistics
%C Brussels, Belgium
%F zhang-etal-2018-visualizing
%X 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.
%R 10.18653/v1/D18-2017
%U https://aclanthology.org/D18-2017
%U https://doi.org/10.18653/v1/D18-2017
%P 96-101

Markdown (Informal)

[Visualizing Group Dynamics based on Multiparty Meeting Understanding](https://aclanthology.org/D18-2017) (Zhang et al., EMNLP 2018)

• Visualizing Group Dynamics based on Multiparty Meeting Understanding (Zhang et al., EMNLP 2018)

ACL

• Ni Zhang, Tongtao Zhang, Indrani Bhattacharya, Heng Ji, and Rich Radke. 2018. Visualizing Group Dynamics based on Multiparty Meeting Understanding. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 96–101, Brussels, Belgium. Association for Computational Linguistics.