@InProceedings{zhang-EtAl:2018:Demos,
  author    = {Zhang, Ni  and  Zhang, Tongtao  and  Bhattacharya, Indrani  and  Ji, Heng  and  Radke, Rich},
  title     = {Visualizing Group Dynamics based on Multiparty Meeting Understanding},
  booktitle = {Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
  month     = {November},
  year      = {2018},
  address   = {Brussels, Belgium},
  publisher = {Association for Computational Linguistics},
  pages     = {96--101},
  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.},
  url       = {http://www.aclweb.org/anthology/D18-2017}
}