Siri and Sentiment Analysis

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     Siri, Apple's iPhone/iPad "genie", lets you use your voice to send messages, schedule meetings, place phone calls, emails, etc. According to Apple, Siri not only understands what you say, it’s smart enough to know what you mean. So what if Siri was used in partner with sentiment analysis to determine the emotional tone in text messages, emails, or social media posts? If Siri could tell you if your message could be construed as having an unintended negative underlying message, or if Siri could serve as a questioning firewall before posting an negative post that could go viral, would it help protect you from potentially severe reputational damage? Rado Kotorov wonders if this implementation of sentiment analysis will help make the world a better place with less conflict and argument, or if it just would leave piles of unread messages in your inbox.
     So how can a machine predict the emotions of messages? This is a challenging question, given that even humans are not entirely perfect in the art of discerning other humans' emotions. Sentences can contain subtleties in various phrases in differing languages, and short answers can also probe problems with sentiment analysis. Sentiment analysis typically uses a way of "scoring" a phrase by the amount of negative or positive words; there is hardly any room for sentiment analysis to determine the meaning behind phrases that mean the opposite of just the words themselves (sarcasm).
     In my opinion, if this technology were to be implemented, sentiment analysis would need to advance to the point of determining nuances in colloquial language and the nature behind how humans communicate in order to be effective. Parent article here.