IBM Watson Tone Analyzer
developer.ibm.com
developer.ibm.com
Quick example, "I hate your guts and I hope you die." -- Hope is picked out and noted as cheerful.
that's why I coupled my model with flow analysis on the mail server end to assign subordination relations between parties when possible.
A general solution is OK for liaisons but that's about it.
The IBM demo appears to be just positioning Watson as a general business concierge here and doesn't seem to be concerned with a true assist on what Gardener calls interpersonal intelligence.
Being able to write concisely and well doesn't necessarily mean you can permeate communication walls.
A valid computer solution, in brief, involves continuous kernel application during the authorship; how the user responds to the system is itself part of the analysis. This isn't just binary sentiment analysis of product reviews using an SVM - that's childs' play compared to this.
Even with the best solution I came up with, it's still just culturally specific ... cultural to the geolocation of the persons and the heritage of the people, but also to the industry itself.
Something that may show weakness in one industry may show wisdom in another, hostility in another, and humility in another.
For instance, say you met someone with whom you had a serious romantic interest. Would you exchange business cards, and then arrange a 9am skype call the following tuesday? It's just all so contextual.
This rabbit hole runs deep.
I'd be interested in whatever else you can talk about. I find this topic interesting and can see the usefulness of it (though I'm imagining something more comprehensive than this demo). The kind of nightmare that I imagined when going into this article though, was some kind of genetic/optimization algorithm that will just iterate on some text until it has achieved the optimal, "most emotionally/etc correct", communication. Obviously, this assumes some highly accurate model of people's emotional perceptions [not to mention, what the words actually mean :)], but I think it's still a somewhat scary thought.
Anyway, would love to hear more about what you're working on.
I didn't finish all the build out, because I got really cold feet in the early pitches ... moved on to other things
should I get back on this? It's always so hard to tell if discouragement is a true representation or just people being internety. I also grossly lack self confidence. I don't know if I need pills, therapy, or what.
I imagine a lot of people could use some kind of OSS sentiment detection, even if it's not perfect.
Try therapy before pills
The synonyms for acknowledge on their example are not very good.
Here is a link to the demo to test it out yourself. http://tone-analyzer-demo.mybluemix.net/
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.
http://cs224d.stanford.edu/syllabus.html
There is a race to create a virtual assistant and do question answering.. the big players are IBM Watson, Apple w/ Siri, Google, Microsoft w/ cortana, facebook M, and Amazon Echo.
Seems like the logical progression, if not full outright automatic generation of messages.
To the GP I'm sure you could 're-tone' many messages, but as presented here the results would likely be unsatisfactory. Doing so effectively would require second- and third-order analysis and now you're getting into Hard Problems.
In fact I wouldn't be surprised if it's already part pf the internal tooling.
You are a retarded goat.
Is apparently a positive sentence.
"We can't blame the economy" is passive aggressive, but it gets coded as green.
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.
Similarly, it says that green means that it's placed in the "writing tone" evaluation category, in that it tries to determine whether the writing comes across as analytical, confident or tentative. More like instructions or analysis and less like judgment or conversation.
It's better to look at the demo in a different way. I mean, if I put your post into the analyzer it tells me that it's impassioned, and of that it's not very cheerful. If I put mine in, it looks very matter of fact. It's more analytical and matter-of-fact.
The two posts imply that kind of difference in tone, and it's pretty cool to see.
It's got a way to go, but trying different examples is interesting.
This is a strange reason to write a tool, and perhaps symptomatic of the corporate culture that sought to produce it.
Teaching people to be nicer would be more interesting, and it's clear it is not dwelling on the right elements since it neglects to detect the overall tone of the email as being problematic.