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

1. DataMiner

2. DataMiner What is DataMiner? Our goal Demo Resultsiterations 1-3 Functionalityafter iteration 3 Iteration 4 Conclusion

3. What is DataMiner? DataMiner is a socialnewsgame. The user mines the underground forarticles. Mineralsrepresent different kinds of articles. The applicationlearnswhicharticles the user likes.

4. Our goal Bringactuality in a playful way. We want toreachgroupswho’sprimaryinterestsaren’trelatedtonews. We want touse the game element topersuade these groupstoreadnews more often.

6. Results Iteration 1 (9/4 – 24/4) 2.45 clicks per article, keystrokesseverelyunderused Balanced ratings Some users never minedanarticle Users didn’tlike the graphics Some minor glitches Users askedfora legenda

7. Results Iteration 2 (25/4 – 3/5) Some users found the help, othersdidn’t Only 9 users 

8. Results Iteration 3 (4/5 – 9/5) On average 8.15 minutes foreachvisit Only 7 users 

9. Iteration 3 Availablefunctionality Miningarticles Rating articles Badges Legend Statistics Improvedgraphics

10. Iteration 4 (10/5 – 23/5) New functionality Invite friends

11. Iteration 4 Goals & Methods Attract more users Measurenumber of users Google analytics Trytofindwhy users aren’tcoming Measureifall users canstill mine andratearticles Make the few users we have come back Google analytics

12. Iteration 4 Results 29 users  41% comes back at leastonce Balancedratings

13. Conclusion The application is easy touse! A reasonableamount of users come back toourapplication. Users find the applicationineffectiveforfindingarticles. (dueto bug) Most users don’tbecome more interested in news.

14. Questions?