docUmberto Grandi, Andrea Loreggia, Francesca Rossi and Vijay
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Umberto Grandi, Andrea Loreggia, Francesca Rossi and Vijay
From Sentiment Analysis to Preference Aggregation Umberto Grandi, Andrea Loreggia, Francesca Rossi and Vijay Saraswat University of Padova and IBM TJ Watson Research Center Umberto Grandi University of Padova What is the collective sentiment about ... ? ...Torino Umberto Grandi University of Padova Aggregation of individual polarities Collective sentiment 40% 60% Umberto Grandi University of Padova A Problem: Multiple Alternatives If preferences are as follows: 21 voters 10 voters 4 voters Umberto Grandi a b b | | | a a b Sentiment analysis: blue! Preference aggregation: red! University of Padova Challenge 1 What preferences/opinions can be extracted from text? partial scores 5-star ratings 4.5 binary comparisons -3 Umberto Grandi University of Padova Challenge 2 How to represent (compactly) the information extracted? Interpersonal incomparability Umberto Grandi Incompleteness University of Padova Challenge 3 How to aggregate the individual information into a collective opinion? Umberto Grandi University of Padova Challenge 4 Is it possible to identify influencers and prevent strategic behaviour? Umberto Grandi University of Padova Challenge 5 How should preference methods be validated? Against real events (predictive ability) Umberto Grandi Axiomatically (Social Choice Theory) University of Padova Challenge 6 How to deal with big data in sentiment/preference analysis? Umberto Grandi University of Padova Thank you! • Challenge 1: what to extract? • Challenge II: compact representation • Challenge III: aggregation • Challenge IV: strategic behaviour • Challenge V: validation • Challenge VI: big data Umberto Grandi University of Padova
