We analyze Debate Threading Models for representing Peer-to-Peer Decentralized Debates. The challenge, we address, is how to structure arguments in debate on a clear topic such that they are informative to the users trying to make up their mind, and such as to foster reciprocal understanding of each of the views in the community. Moreover, to enable the participation of average skilled users, the technique for inputting the arguments may have to be simple (ie, close to the common practice, which is a subjective criteria). Knowledge representation for serving human users has been an important area of study in Computer Science and Artificial Intelligence. The area has grown significantly with conferences on topics such as ontologies, collaborative filtering, semantic web, and argument maps. We study and compare the various existing structures for representing complex knowledge in understandable forms, focusing on their applicability to decentralized debates with arguments from general users. We believe that this is the first kind of work that deals with the issue above.