[aisofteng]

I'm always a little wary of the robustness of sentiment analysis; in my experience, if you take the time to check sentiment analysis results sentence by sentence, you will find a high error rate.

I haven't confirmed by looking at the source, but my suspicion is that either most sentiment analysis implementations are rule based or are not well tuned.

My go-to example is IBM Watson's sentiment analysis service rating "I hope you die" as very positive because the sentence is categorized as "hopeful". Which I suppose it is, technically, and perhaps this is a case where I'm expecting too much because recognizing this particular example as having a negative sentiment requires much human abstract reasoning and inference, but the example remains nonetheless because real-world language usage that isn't dry and technical is rife with these sorts of linguistic usages.