Argumentation Mining: Techniques and Emerging Trends


Shobhit Sinha, Research Scholar, Bineet Kumar Gupta, Associate Professor, Rajat Sharma, Research Scholar
Department of Computer Applications, Shri Ramswaroop Memorial University, Lucknow, Uttar Pradesh, India.


By Argument we mean persuasion of a reason or reasons in support of a claim or evidence. In Artificial Intelligence computational argumentation is the field dealing with computational logic upon which many models of argumentation have been suggested. The goal of Argumentation Mining is to automatically extract structured arguments from the unstructured text. It has the potential of extracting information from web and social media, making it one of the most sought after research area. Some recent advances in computational logic and Machine Learning methods do provide a new insight to the applications for policy making, economic sciences, legal, medical and information technology. Different models have been proposed for argumentation mining with different machine learning methods applied on the argumentation frameworks proposed for this particular mining task. In this survey article we will review the existing systems and applications and will cover the three categories of argumentation models and a comparative table depicting the most frequently applied ML method. This survey paper will also cover the various challenges of the field with the new potential perspectives in this new emerging research area.