My initial impression is it doesn't seem analyze groups of words very well. It will pick emotional words out of the middle of a sentence and apply the emotion to the whole text, when the context of the sentence changes the meaning of the word.<p>Quick example, "I hate your guts and I hope you die." -- Hope is picked out and noted as cheerful.
Looks like it's doing emotional classification. Seems more geared towards a single word approach versus strong contextual classification.<p>The synonyms for acknowledge on their example are not very good.<p>Here is a link to the demo to test it out yourself.
<a href="http://tone-analyzer-demo.mybluemix.net/" rel="nofollow">http://tone-analyzer-demo.mybluemix.net/</a>
It doesn't deal with negation very well – the phrase "I have never had a sad day with you" is marked as negative because it contains the word "sad".
I think IBM really inspired people with Watson, but they have failed to productize it and now they are using "Watson" as a marketing label for any A.I. related technology at all -- be it something very good that they started work on years ago (Speech Recognition) or something really bad that they aquired like AlchemyAPI.
It's interesting and I will keep it bookmarked for occasional use, but the classification into emotional, social and writing tones seem very arbitrary. At least part of the problem is that it seems to be working on single words, most of which are weighted more toward one classification or another based on aggregate use rather than any real context. Tools like this rarely seem to do any analysis at the phrase level, even though phrases of two or three words often contribute significant substantive or structural context. This is odd considering that we already have techniques for identifying statistically improbable phrases as intermediate lexical units (often used for detecting plagiarism).<p>Is anyone aware of work going on in this area? I'm quite interested in lexical analysis, but I'm wary of investing a lot of time just to reinvent the wheel.
Is there a way to 're-tone' a message, eg: making someone sound more aggressive?<p>Seems like the logical progression, if not full outright automatic generation of messages.
I can see a more advanced version of this being deployed as part of automated admin packages for commenting sites such as reddit and HN. Any comments of sufficiently negative tone gets auto-downvote/hidden/flagged, etc.<p>In fact I wouldn't be surprised if it's already part pf the internal tooling.
I kind of like it how the example on this page is helping someone make their email more harsh, when it's already using exclamation points and starting sentences with "but" and is already heeps of negative.<p>"We can't blame the economy" is passive aggressive, but it gets coded as green.<p>Not being passive aggressive is good, but perhaps writing the sample email in a way that makes people want to work for this person would be a good idea instead.