  The massive amount of text data on the web has facilitated research on the
quantitative analysis of public opinion, which could not be visualized earlier.
In this paper, we propose a new opinion dynamics theory. This theory that is
intended to explain agreement formation and opinion breakup division in opinion
exchanges on social media such as Twitter. With the popularization of the
public network, we have become able to communicate with instantaneity and
interactivity beyond the temporal and spatial constraints.Research on
quantitatively analyzing the distribution of opinion on public opinion that has
not been visualized so far utilizing massive web text data is progressing.Our
model is based on the Bounded Confidence Model, that expresses opinions in as
continuous quantity values. However, in the Bounded Confidence Model, it was
assumed that people with different opinions move not in disregard but ignoring
opinions. Furthermore, in our theory, it modeled so that it can expresser model
incorporates the influence from of the external pressure outside and the
phenomenon depending on the surrounding situation.
