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The massive amount of text data on the web has facilitated research on thequantitative analysis of public opinion, which could not be visualized earlier.In this paper, we propose a new opinion dynamics theory. This theory that isintended to explain agreement formation and opinion breakup division in opinionexchanges on social media such as Twitter. With the popularization of thepublic network, we have become able to communicate with instantaneity andinteractivity beyond the temporal and spatial constraints.Research onquantitatively analyzing the distribution of opinion on public opinion that hasnot been visualized so far utilizing massive web text data is progressing.Ourmodel is based on the Bounded Confidence Model, that expresses opinions in ascontinuous quantity values. However, in the Bounded Confidence Model, it wasassumed that people with different opinions move not in disregard but ignoringopinions. Furthermore, in our theory, it modeled so that it can expresser modelincorporates the influence from of the external pressure outside and thephenomenon depending on the surrounding situation.

Opinion Dynamics Theory for Analysis of Consensus Formation and Division of Opinion on the Internet