DataMiner Presentation 2011 05-24 v0.3

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Presentation for the course of Human-Computer Interaction.Our final iteration of our social news application.

Transcript

DataMiner

DataMiner

• What is DataMiner?• Our goal• Demo• Results iterations 1-3• Functionality after iteration 3• Iteration 4• Conclusion

What is DataMiner?

DataMiner is a social newsgame.

The user mines the underground for articles. Minerals represent different kinds of articles.

The application learns which articles the user likes.

Our goal

Bring actuality in a playful way.

We want to reach groups who’s primary interests aren’t related to news.

We want to use the game element to persuade these groups to read news more often.

Results

• 2.45 clicks per article, keystrokes severely underused

• Balanced ratings• Some users never mined an article• Users didn’t like the graphics• Some minor glitches• Users asked for a legenda

Iteration 1 (9/4 – 24/4)

Results

• Some users found the help, others didn’t

• Only 9 users

Iteration 2 (25/4 – 3/5)

Results

• On average 8.15 minutes for each visit• Only 7 users

Iteration 3 (4/5 – 9/5)

Iteration 3

• Mining articles• Rating articles• Badges• Legend• Statistics• Improved graphics

Available functionality

Iteration 4 (10/5 – 23/5)

• Invite friends

New functionality

Iteration 4

• Attract more users– Measure number of users– Google analytics

• Try to find why users aren’t coming– Measure if all users can still mine and rate articles

• Make the few users we have come back– Google analytics

Goals & Methods

Iteration 4

• 29 users • 41% comes back at least once• Balanced ratings

Results

Conclusion

• The application is easy to use!• A reasonable amount of users come back to

our application.• Users find the application ineffective for

finding articles. (due to bug)• Most users don’t become more interested in

news.

Questions?

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