3 ms·

According to this [1] BBC News article from last year, a French company called Spotter [2] offers an analytics tool that they claim can identify sarcasm in web

According to this [1] BBC News article from last year, a French company called Spotter [2] offers an analytics tool that they claim can identify sarcasm in web and social media comments. Supports multiple languages to 80% accuracy. I've no idea if it works and their site is rather light on detail. [1] http://www.bbc.co.uk/news/technology-23160583 http://www.bbc.co.uk/news/technology-23160583 [2] http://spotter.com/ http://spotter.com/

vog 12y ago
It would be interesting to know how this algorithm behaved on fundamentalist texts. (see Poe's law, https://en.wikipedia.org/wiki/Poe%27s_law https://en.wikipedia.org/wiki/Poe%27s_law)
opium_tea 12y ago
This video suggests their early prototypes required some further calibration: https://www.youtube.com/watch?v=mSy5mEcmgwU https://www.youtube.com/watch?v=mSy5mEcmgwU
Create 12y ago
DARPA / IBM http://www.research.ibm.com/cognitive-computing/index.shtml http://www.research.ibm.com/cognitive-computing/index.shtml
rainforest 12y ago
This paper appears to claim up to 91% accuracy (precision) [1] by looking at hashtags, with a description of the approach they use (and a link to the software). The approaches probably aren't directly comparable since one depends on hashtags while the other doesn't though. [1] : https://gate.ac.uk/sale/lrec2014/arcomem/sarcasm.pdf https://gate.ac.uk/sale/lrec2014/arcomem/sarcasm.pdf
eli_gottlieb 12y ago
Yeah, really. It's creating a whole human mind that's hard. Particular, isolated tasks or features about particular things in particular cultures are not actually that hard to learn/classify in themselves, as your data corpus will be more uniform than if you were trying to perform some more general cognition across a wider variety of contexts. More uniformity makes it easier to learn.

3 ms·

According to this [1] BBC News article from last year, a French company called Spotter [2] offers an analytics tool that they claim can identify sarcasm in web

by andyjohnson0 12y ago

vog 12y ago
It would be interesting to know how this algorithm behaved on fundamentalist texts. (see Poe's law, https://en.wikipedia.org/wiki/Poe%27s_law https://en.wikipedia.org/wiki/Poe%27s_law)
opium_tea 12y ago
This video suggests their early prototypes required some further calibration: https://www.youtube.com/watch?v=mSy5mEcmgwU https://www.youtube.com/watch?v=mSy5mEcmgwU
Create 12y ago
DARPA / IBM http://www.research.ibm.com/cognitive-computing/index.shtml http://www.research.ibm.com/cognitive-computing/index.shtml
rainforest 12y ago
This paper appears to claim up to 91% accuracy (precision) [1] by looking at hashtags, with a description of the approach they use (and a link to the software). The approaches probably aren't directly comparable since one depends on hashtags while the other doesn't though. [1] : https://gate.ac.uk/sale/lrec2014/arcomem/sarcasm.pdf https://gate.ac.uk/sale/lrec2014/arcomem/sarcasm.pdf
eli_gottlieb 12y ago
Yeah, really. It's creating a whole human mind that's hard. Particular, isolated tasks or features about particular things in particular cultures are not actually that hard to learn/classify in themselves, as your data corpus will be more uniform than if you were trying to perform some more general cognition across a wider variety of contexts. More uniformity makes it easier to learn.