Tuesday, July 17, 2012

Diving into the Statistics...Astronomy

Yesterday we looked at what the results told us on a broad scale.  We learned that offering tangible rewards (e.g., cash) was the most sure-fire way to achieve a successful citizen science project.  But we also know that the different scientific fields create projects under different constraints and cater to people with different interest.

Let's look at astronomy first.  It's one of the most popular types of projects available and also one of the most diverse.  A lot falls under this category with participants performing a wide variety of tasks.  So it should be no surprise if there is also wide variety in the importance of success factors for each individual project.  But let's look at what the numbers tell us.

From a scholarly success point of view, we can see that the strongest correlation is with Educate the User.  Given the nature of the field not much can be discovered without either significant training or concerted design work to succeed.  Unlike ecology projects you can't just send a person into the backyard with a magnifying glass; instead you either need to provide access to advanced telescope data along with tools for interpreting it, or you need to train individuals how to observe and measure stars from their backyard.  The second requires much education and training, and the first means much explaining is required for users to participate.

Additionally, it is these more complex astronomy projects that achieve the most scholarly success.  This means that easy to understand projects (requiring little additional education) don't have much potential for new knowledge.  But more complex projects with significant teaching requirements also have educational opportunities as a side benefit.  So this success factor is not just a predictive factor, but also a side-effect of the project's very nature.

Entertain 0.095559984
Reward -0.080876458
Challenge 0.183599383
Educate 0.368265236
Motivate the User 0.024092987
Create a Community 0.186135395
Interact in Real Time 0.183557797
Provide Feedback 0.034732258
Offer Excitement -0.310943178
Encourage Dialogue 0.091740298
Provide Data Access 0.27963916
Allow for Errors 0.076900829
Be Audacious 0.272500062
Stay Focused -0.373308726
Make it Convenient -0.02391735
Make Learning Easy 0.231746537
Make Participating Easy 0.113893409

But now let's look at a different success indicator...general popularity.  Here we get a surprisingly different result.  After the importance of offering a reward (previously discussed) the two biggest factors are to Offer Excitement and Be Audacious.

Entertain -0.351447347
Reward 0.576650297
Challenge 0.30922189
Educate -0.341196228
Motivate the User 0.06370121
Create a Community -0.165903482
Interact in Real Time -0.374093447
Provide Feedback 0.140734236
Offer Excitement 0.442401972
Encourage Dialogue 0.088954375
Provide Data Access -0.420434771
Allow for Errors -0.554451346
Be Audacious 0.429358299
Stay Focused -0.366548773
Make it Convenient -0.324426406
Make Learning Easy -0.377610427
Make Participating Easy -0.477168855

What makes these two factors so important?  Since we are looking at general public popularity these are two factors that would create the most "buzz" about the project. It's most exciting to the average person, the media publicize these projects more since they can easily excite their readership about it, and by working on big concepts they are easier to explain.  So they attract more press, more readers, and more participants.  This doesn't necessarily make them academically successful, but it does provide a steady pool of people potentially interested in joining.  So all designers need to do is keep that energy moving to actual participation, and the project becomes successful.

It should also be noted that "Be Audacious" and "Offer Excitement" can be very similar concepts that overlap significantly.  But there are differences (as described in my previous posts here and here), and while in many cases the audaciousness can lead to excitement, I did separate them on purpose.  It just shows that the overlap must be accounted for, and that project designers can often incorporate multiple success factors even if they focus on only a few points.

Of course, all this deals with only Astronomy projects.  Does it also apply to Ecology projects or Distributed Computing projects?  Check in tomorrow and find out!


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