Assessing the impact of social network on the formation and evolution of collective opinion in integrated intelligent argumentation with social network

Massive online argumentation platforms can potentially capture the decision rationale and collective intelligence. Although significant advances have been made in their models, algorithms, and applications, the role of social networking in shaping the formation and evolution of opinions in cyber-argumentation remains under-explored. Social networking aspects like friends and follows relationships among users in cyber argumentation can reveal the patterns, shifts, and true relationships between the users in a discourse that influence the collective decision-making process. However, there are currently no systematic methods for assessing the impacts of social networks on the formation and evolution of collective opinions in cyber-argumentation. In this research, we propose a novel method to quantify the impact of social networking on cyber-argumentation. We investigate three types of impacts: directional impact, mutual impact, and social group impact. These different measures help quantify what the social group of a person thinks about his or her opinions and their impacts on their arguments. Using these impact measures, we developed an algorithm to detect the pseudo-supporters of an individual in an argumentation network. Furthermore, we also study the impact of the social network of users on significant shifts in collective opinion using the social group impact and the strength of the social connection of users in argumentation. The proposed methods and algorithm have been implemented within our intelligent cyber-argumentation system with social networking. Our empirical evaluations demonstrate the effectiveness of these quantification methods, detection of pseudo-supporters, and assessing the impact of social networks on collective opinion shifts in cyber-argumentation.