Analytics in Virtual Worlds Hilary Mason SL: Ann Enigma Johnson & Wales University

Virtual World Analytics

how effective is this interaction?

what about this one?

what’s possible here?

system architecture sensor sensor sensor Second Life Web Gateway Database collect data data view data

aggregate metrics

space-centered visualizations

What is this person doing?

What is this person doing?

user-centered metrics Models of user behavior allow humans to understand how people are using virtual worlds. Currently, we can model: dancing, chatting, listening (to a presentation), shopping, creating content

Models of user behavior allow humans to understand how people are using virtual worlds.

Currently, we can model: dancing, chatting, listening (to a presentation), shopping, creating content

group-centered metrics

qualitative metrics Integrate surveys/polls Commenting system (optionally integrates with blogs) Visual surveys (each click counts) Position-based polling

Integrate surveys/polls

Commenting system

(optionally integrates with

blogs)

Visual surveys (each click

counts)

Position-based polling

experiential assessment

What’s NEXT ?

What’s

NEXT ?

Can we generalize?

similar metrics on many platforms

Open Standards Standards will allow us to draw conclusions across worlds and across platforms.

Standards will

allow us to draw

conclusions across

worlds and across

platforms.

social media needs metrics, too

In 2008 we’ll see an Explosion in Virtual Worlds Platforms

join in!

thank you! Creative Commons Hilary Mason Ann Enigma [email_address] http://www.3greeneggs.com http://www.jwuiml.org

Creative Commons