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> I find it hard to see how detecting and eliminating sarcasm requires a theory of mind. It requires some association between various stylistic elements and the

> I find it hard to see how detecting and eliminating sarcasm requires a theory of mind. It requires some association between various stylistic elements and the concept of sarcasm. I am quite certain that detecting sarcasm can't be done based on stylistic elements" and requires some (even if implicit) estimation of what the author is thinking that contrasts with what is being said. E.g. a relevant example I have actually seen in doing sentiment analysis on tweets to evaluate how customers perceive a company is "#CompanyName Got my order delivered in just under three hours. Thank you for great service! thumbsup-emoji" - now is this a positive review or sarcasm? And the thing is, you can't tell from the message by itself, you need an understanding of the customers' expectation (guess you might call it "a theory of mind") that for a pizza chain this is obviously sarcasm, but for a web store that sells some electronics the same thing would actually mean a fast delivery and great service. IMHO sarcasm detection is mostly about 'world knowledge' about what the implied expectations are, and not about stylistic elements at all.

megablast 4y ago
You are assuming it is 100% perfect at detecting sarcasm at all times. There is no reason for this to be true.
PaulDavisThe1st 4y ago
Disagree. If you have determined that a common element in reviews is a reference to delivery of goods or services within a given timeframe, and can identify that most of the quantitative descriptions of the timeframe are relatively short ... then coming across one that uses a much larger timeframe but is still positive will be quite noticeable. This is actually typical of the problem with far, far too many people's interpretation of what language models are doing. The process I've described requires only a representation of language behavior. The LM can be said to understand how people talk (write) about a thing, but there is no knowledge of anything beyond language behavior.

megablast 4y ago

You are assuming it is 100% perfect at detecting sarcasm at all times. There is no reason for this to be true.

PaulDavisThe1st 4y ago

Disagree. If you have determined that a common element in reviews is a reference to delivery of goods or services within a given timeframe, and can identify that most of the quantitative descriptions of the timeframe are relatively short ... then coming across one that uses a much larger timeframe but is still positive will be quite noticeable. This is actually typical of the problem with far, far too many people's interpretation of what language models are doing. The process I've described requires only a representation of language behavior. The LM can be said to understand how people talk (write) about a thing, but there is no knowledge of anything beyond language behavior.