Design of Mobile Service of Intelligent Large-Scale Cyber Argumentation for Analysis and Prediction of Collective Opinions

Abstract

Issues of national and international importance attract the attention of millions of people who want to share their opinions online. These discussions among a large number of people contain rich information, from which we want to extract the crowd wisdom and collective intelligence. Most of these discussions happen in social media platforms such as Facebook and Twitter or debate-centric platforms. Social media platforms are accessible but not structured in a way to effectively facilitate these large-scale discussions, leading many discussions to be fragmented, difficult to follow, and nearly impossible to analyze collective opinions. Debate-centric platforms represent issues with binary solutions and modest analytics. In the cyber-argumentation, a sub-field of AI, argumentations platforms have been developed to facilitate online discussion effectively. These platforms provide structured argumentation frameworks, which allows for meaningful analytics models to mine the argumentation. However, few platforms have mobile service application and those that do provide only basic statistical analytics. In this paper, we present the design of a mobile application service to support intelligent cyber argumentation. This service is designed to facilitate large-scale discussion and report complex analytics on a handheld screen size. The platform has several integrated analytical models, which use AI techniques, to capture collective opinions, detect opinion polarization, and predict missing user opinions. An example of a large-scale discussion is used to demonstrate the effectiveness of bringing intelligent cyber-argumentation into the mobile space.