Gender prediction based on information about how a person plays a game
#1 Members - Reputation: 100
Posted 29 March 2012 - 03:53 PM
I am doing a research project (master thesis) where I attempt to use machine learning and game play data collected from a modified open-source version of Super Mario. The hypothesis is that men and women play differently and that this difference can somehow be extracted as features used to learn a "gender classifier".
One can imagine that it may be possible to transfer the concept to other software applications and to extract other information than gender about users.
I am curious what you think about the project, and if you have time: play the game for 5 minutes and generate some data.
The game client is Java-based and can be found here:
http://www.masterofdebian.com/mario
/Lasse
#2 Members - Reputation: 952
Posted 29 March 2012 - 04:08 PM
#3 Members - Reputation: 100
Posted 29 March 2012 - 04:17 PM
I tried three times, but the controls seemed to work sporadically: sometimes having no effect, sometimes seeming to get 'stuck down', sometimes taking an action I didn't press the button for (or, perhaps, doing what I asked but with a several-second delay). Hopefully this didn't generate too much spurious data for you, sorry!
That is perfectly fine! I agree that the game controls are not superb, and I did not program that part myself. The game is a modified version of the MarioAI from http://www.marioai.org/.
There should be no delay generated by submitting game play data as it occurs on a separate thread.
#6 Members - Reputation: 160
Posted 31 March 2012 - 01:14 PM
My only advice would be to think about including context in your measurements. Rather than just controller inputs, consider measuring percentage of bricks smashed, percentage of time spent on ground, number of times player got within n pixels of an enemy without killing the enemy, percentage of enemies squished, etc..
Also, breaking each level up in to distinct areas, and keeping statistics about each area, might also help distinguish male from female players.
#7 Members - Reputation: 206
Posted 31 March 2012 - 02:31 PM
I am doing a research project (master thesis) where I attempt to use machine learning and game play data collected from a modified open-source version of Super Mario. The hypothesis is that men and women play differently and that this difference can somehow be extracted as features used to learn a "gender classifier".
Immediately, my question would be "to what end"? As long as this information isn't empirically true (which it never is, when dealing with people), it's pretty useless. There's already a vast understanding about how women play games compared to men, but it's highly generalizing and you cannot use it to figure out the gender of the person.
To put it simply: Too many men play like women and too many women play like men.
As for how women actually tend to play compared to men, it's mostly about attention span. Women tend to have a playstyle that reflects how they appear to the outside world (such as being diplomats, managers and strategists), whereas men tend to play in terms of how the world look to them (down-and-dirty, completionists, tacticians, bragging rights, etc). But that's pretty much it. The rest is pure individuality.
Anyways, just my 2 cents.
#8 Members - Reputation: 100
Posted 31 March 2012 - 03:57 PM
Interesting topic. Please post a copy of your paper once it's done. I have done similar work analyzing blog postings and newspaper articles. My only advice would be to think about including context in your measurements. Rather than just controller inputs, consider measuring percentage of bricks smashed, percentage of time spent on ground, number of times player got within n pixels of an enemy without killing the enemy, percentage of enemies squished, etc.. Also, breaking each level up in to distinct areas, and keeping statistics about each area, might also help distinguish male from female players.
I will post my paper here when it is done later this summer, and thanks for the contributions so far.
I do collect the variables you mention and many more, except how close players get to enemies without killing them; it is a feature I will try to add, since I can use the other data gathered to produce that particular feature.
#9 Members - Reputation: 100
Posted 31 March 2012 - 04:05 PM
#10 Members - Reputation: 160
Posted 31 March 2012 - 09:58 PM
I am doing a research project (master thesis) where I attempt to use machine learning and game play data collected from a modified open-source version of Super Mario. The hypothesis is that men and women play differently and that this difference can somehow be extracted as features used to learn a "gender classifier".
Immediately, my question would be "to what end"? As long as this information isn't empirically true (which it never is, when dealing with people), it's pretty useless. There's already a vast understanding about how women play games compared to men, but it's highly generalizing and you cannot use it to figure out the gender of the person.
You can't use your imagination a little? There are all kinds of reasons you might want to know the gender of the person sitting in front of a machine. Targeted advertising, for one. Maybe targeted rewards (a pink shotgun instead of a camo one?), or even changes to storylines based on how a player is percieved to act.
And there's always the "plays like a girl" badge on the PS3 that's currently not an option.
#11 Crossbones+ - Reputation: 1448
Posted 01 April 2012 - 02:33 AM
I tried three times, but the controls seemed to work sporadically: sometimes having no effect, sometimes seeming to get 'stuck down', sometimes taking an action I didn't press the button for (or, perhaps, doing what I asked but with a several-second delay). Hopefully this didn't generate too much spurious data for you, sorry!
That is perfectly fine! I agree that the game controls are not superb, and I did not program that part myself. The game is a modified version of the MarioAI from http://www.marioai.org/.
There should be no delay generated by submitting game play data as it occurs on a separate thread.
I believe this may skew your results, i attempted to play as well, and the controls being delayed/ignored is most likly going to really effect your results. unless your goal also includes seeing how different gender's will react to unresponsive controls.






