Argument Book

Opinion mining is a prevalent research issue in many domains. In the financial domain, however, it is still in the early stages. Most of the researches on this topic only focus on the coarse-grained market sentiment analysis, i.e., 2-way classification for bullish/bearish. Thanks to the recent financial technology (FinTech) development, some interdisciplinary researchers start to involve in the in-depth analysis of investors' opinions. These works indicate the trend toward fine-grained opinion mining in the financial domain.

​This monograph poses a series of key problems of evidential reasoning and argumentation. It then offers solutions achieved by applying recently developed computational models of argumentation made available in artificial intelligence. Each problem is posed in such a way that the solution is easily understood. The book progresses from confronting these problems and offering solutions to them, building a useful general method for evaluating arguments along the way.

This book offers a discussion of the kalām cosmological argument, and presents a defence of a version of that argument after critically evaluating three of the most important versions of the argument.