Analyze Your HN Posts with Watson User Modeling

Ironically, this really did feel like a machine based cold-reading.

Maybe they all come out a bit like that?

        function redcom(){ ! [ -z "$2" ] && i="&after=$2" || i=""; data=$(curl -s "https://www.reddit.com/user/${1}/comments.json?count=100${i}"); j=$(jq -e -r '.data["after"]' <<<$data); echo $j; (jq -e -r '.data["children"][]["data"]["body"]' <<<$data)>>${1}-redcom.txt; echo $(echo -e $data|wc -l) lines; ( [ "$j" = "null" ] || [ -z "$j" ] ) || redcom $1 $j ;} ;

Never user/heard of jq before, it's a pretty nice tool.

The IBM documentation doesn't really say anything about how these numbers are calculated

and using the sample Node project to show the results. I am still exploring it myself :p

To some extent, our personalities are our personalities. We behave, on some level, the same in every context and in every community. But the extent to which that's the case is up for debate. We probably use different approaches, or if you prefer, we show different aspects of our personalities, in different contexts and in front of different groups. That's why it's extremely difficult to take one context (HN, for instance), and extrapolate universal characteristics from it.

Even within the set of HN history, I got some oddball results. For instance, Watson considers me very "Fiery" (51%) here. There are plenty of areas in my life in which the word "Fiery" makes a bit of sense. HN isn't one of them.

When the results are right, they're just "right" so you should accept them, when they're wrong they're actually also right by whatever magical hamster wheel is operating inside of the thing and you just don't "get it".

The problem is that humans like to have some clue as to how the results were derived, something easy to explain that gets the gist across. Something like "Watson counted all the words you use and compared them to different reference lexicons to arrive at the score". This provides a little bit of context so we understand the semantics of the result and how to consider them and reason with them.

But for all we know the results we're seeing are from some arbitrary stochastic method:

openness=rand(90,99) harmony=rand(90,100)

etc.

For things like this to be accepted by the users (humans) there needs to be a quick explanation for how this works otherwise we get head scratchers.

Meanwhile, you can do a search on "IBM System U" (the project's not-so-internal code name.) This particular slideshare.net prez has some great info on the methodology, validation tests and references: http://slidesha.re/1ri0vPV

You can read the words they wrote but you cannot perceive the tone they wrote it in....I dont think this is helpful and may dismiss candidates that are otherwise perfect except when Watson analyzes them.

This sounds very dangerous to me. I assume when recruiters and/or lead engineers decide to reach out to me via LinkedIn, they did their homework on me. I purposely link to enough stuff for them to realize "smtddr" is my handle. The same blog & youtube channel in my HN profile is also in my LinkedIn. But I expect a human to look, not some computer judging me. I can totally see people getting lazy and just doing stuff like only filtering for people who rate 80% on openness or something. Then everyone will start grooming their posts simply to get positive results... then someone will create a social website that claims to block those scanners so people can say whatever they want.

It just forces people underground and the filters won't work anymore since at that point you might as well assume everyone is gaming the system.

(fwiw, I'm also against standardized tests. Anything that forces a whole group of people to start grooming themselves for a very specific measurement kills diversity, imho. Since the very term "standardized" kinda goes against the concept of diverse... and people become lazy and just rely on such tests to make or break the deal)

http://www.redditinvestigator.com/

        function redcom(){ ! [ -z "$2" ] && i="&after=$2" || i=""; data=$(curl -s "https://www.reddit.com/user/${1}/comments.json?count=100${i}"); j=$(jq -e -r '.data["after"]' <<<$data); echo $j; (jq -e -r '.data["children"][]["data"]["body"]' <<<$data)>>${1}-redcom.txt; echo $(echo -e $data|wc -l) lines; ( [ "$j" = "null" ] || [ -z "$j" ] ) || redcom $1 $j ;} ;

For more information on systematic associations between personality and individual differences in word use, please refer to studies like Tal Yarkoni, "Personality in 100,000 words: A Large scale analysis of personality and word use among bloggers", 2010