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Weaving Intangible Software Value

I am quite pleased with myself this morning. Starting at 9:15 am and working through 11:29 am, I wrote around 200 lines of code. You may scoff at this, and say that you can write better, more elegant, and superior code to me, and you’d probably be right.

However, the code that I wrote does something special. It leverages data repositories available of names (of people) and through some elegant magic of statistics and frequencies, can tell you with very high precision whether an encountered first name is that of a male, or a female, or unknown (which I’ll put in a queue for further analysis).

Laugh you may. Ha ha.
I’ll laugh along with you.

After all, why would someone want the computer to tell them whether a name is mostly associated with males or females? Shahzad, come on man.. don’t waste your time on stuff like this!

However, think for a second…. and wipe that grin off your face my friend. This (gender identification via names) is the type of capability that makes business people very happy. Associating demographics with individuals can boost the value of targeted advertising by 100 times! Carry out a quick survey of CPM costs online, and you’ll notice a huge difference between the cost of adverts on those sites that can qualify the users and viewers via demographic information, and those that do not. It’s the difference between 7 cents per thousand impressions and 14 dollars per thousand impressions (which is what my business partner’s very astute observation and equally diligent survey has demonstrated to me).

.. and why not? If I was paying someone to show an advertisement, I’d consider the money much more well spent if I knew the profile of the individuals that the advertisements were shown to. Even better, if you could only show adverts to those people who meet a pre-selected profile, you’d be my bestest (sic) advertisement-based content-serving site ever!

Pardon my (hopefully infectious) good humour. I’m going to grab a nice cup of tea to celebrate!

  1. Tola
    October 8th, 2009 at 12:00 | #1

    Shazad u r right, its a big deal!!

  2. October 8th, 2009 at 12:44 | #2

    Thank you Tola,
    It’s one step in a long journey. I’ve been putting together this humongous code-base, and a very ambitious architecture, with the help of a few friends. It’s always just tantalizingly out of reach, but comes so much closer each day.

    It reminds of that old question that enquires ‘how would you go about eating an elephant’ (with the cryptic answer, ‘one bite at a time’).


    – Shahzad

  3. fazel
    October 8th, 2009 at 23:21 | #3

    Tola :
    Shazad u r right, its a big deal!!

    Hi Shahzad,
    it’s nice job. Your algorithm take a word as input and identify it’s male,female oo unknown?
    You might you use a corpus, DB , or parser? How ever, it would be more interesting to identify the gender of text writer. i.e for a given text, identify writer is: m,f, or unknown.


  4. October 9th, 2009 at 04:31 | #4

    You’re a natural person for me to work on this problem with. We should consider putting in a funding grant to jointly tackle this task.

    There are also other interesting demographics that we can try and identify (like age, and education level) based on writing style.

    I’m travelling for a few days, but when I return, we should have a coffee to discuss this.

    – Shahzad

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