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Sentiment Analysis of microblog feeds has attracted considerable interest inrecent times. Most of the current work focuses on tweet sentimentclassification. But not much work has been done to explore how reliable theopinions of the mass (crowd wisdom) in social network microblogs such astwitter are in predicting outcomes of certain events such as election debates.In this work, we investigate whether crowd wisdom is useful in predicting suchoutcomes and whether their opinions are influenced by the experts in the field.We work in the domain of multi-label classification to perform sentimentclassification of tweets and obtain the opinion of the crowd. This learntsentiment is then used to predict outcomes of events such as: US PresidentialDebate winners, Grammy Award winners, Super Bowl Winners. We find that in mostof the cases, the wisdom of the crowd does indeed match with that of theexperts, and in cases where they don't (particularly in the case of debates),we see that the crowd's opinion is actually influenced by that of the experts.

Event Outcome Prediction using Sentiment Analysis and Crowd Wisdom in Microblog Feeds