Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: On the b, there is always a need to aggregate opinions from the crowd (as in posts, social networks, forums, etc.). Different mechanisms have been implemented to capture these opinions such as "Like" in Facebook, "Favorite" in Twitter, thumbs-up/down, flagging, and so on. Hover, in more contested domains (e.g. Wikipedia, political discussion, and climate change discussion) these mechanisms are not sufficient since they only deal with each issue independently without considering the relationships beten different claims.  can view a set of conflicting arguments as a graph in which the nodes represent arguments and the arcs beten these nodes represent the defeat relation. A group of people can then collectively evaluate such graphs. To do this, the group must use a rule to aggregate their individual opinions about the entire argument graph. Here,  present the first experimental evaluation of different aggregation rules presented in the literature.  use randomized controlled experiments to investigate which rules people consider better at aggregating opinions under different conditions. Our analysis reveals a number of factors, not captured by traditional formal models, that play an important role in determining the efficacy of aggregation. These results help bring formal models of argumentation closer to real-world application.
['Edmond Awad', 'Jean-François Bonnefon', 'Martin Caminada', 'Thomas W. Malone', 'Iyad Rahwan']
I am writing a research paper on a idea Experimental Assessment of Aggregation Principles in Argumentation-enabled Collective Intelligence
[{"from": "human", "value": "I am writing a research paper on a idea Experimental Assessment of Aggregation Principles in Argumentation-enabled Collective Intelligence"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: On the b, there is always a need to aggregate opinions from the crowd (as in posts, social networks, forums, etc.). Different mechanisms have been implemented to capture these opinions such as \"Like\" in Facebook, \"Favorite\" in Twitter, thumbs-up/down, flagging, and so on. Hover, in more contested domains (e.g. Wikipedia, political discussion, and climate change discussion) these mechanisms are not sufficient since they only deal with each issue independently without considering the relationships beten different claims.  can view a set of conflicting arguments as a graph in which the nodes represent arguments and the arcs beten these nodes represent the defeat relation. A group of people can then collectively evaluate such graphs. To do this, the group must use a rule to aggregate their individual opinions about the entire argument graph. Here,  present the first experimental evaluation of different aggregation rules presented in the literature.  use randomized controlled experiments to investigate which rules people consider better at aggregating opinions under different conditions. Our analysis reveals a number of factors, not captured by traditional formal models, that play an important role in determining the efficacy of aggregation. These results help bring formal models of argumentation closer to real-world application."}]