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State of the art benchmarks for Twitter Sentiment Analysis do not considerthe fact that for more than half of the tweets from the public stream adistinct sentiment cannot be chosen. This paper provides a new perspective onTwitter Sentiment Analysis by highlighting the necessity of explicitlyincorporating uncertainty. Moreover, a dataset of high quality to evaluatesolutions for this new problem is introduced and made publicly available.

Sentiment Uncertainty and Spam in Twitter Streams and Its Implications for General Purpose Realtime Sentiment Analysis