From sentiment analysis to preference aggregation

Current sentiment analysis techniques are good enough when predicting the opinion of a community of individuals over one item, but they may produce wrong or inaccurate results when several possibly correlated items are under consideration. We propose to exploit and adapt formalisms, methods, and tools from knowledge representation and voting theory to generalize sentiment analysis and obtain an accurate definition of collective sentiment about multiple items.