Analysis of Local Assembly Decision-Making Process Using Facet LSTM Model

The objective of the study is to facilitate understanding of lengthy and complicated public discussions through a review of the meeting minutes from a local assembly and to derive from them distilled information using a big data machine learning model. To this end, we take the meeting minutes of the 7th basic assembly of Jin-gu Council in Busan and analyse three attributes: purpose of remark, presence of disagreement, and cause of conflict, as manifested throughout the discussion process through to the final decision making.