I got a nice link some days ago. On qulpa.com one can register items borrowed or lent to remind friends of the debts or mange your own debts. That’s a nice and handy thing, especially for managing computer games 😉 Best of all, the company was founded by a friend of mine 😀
Second talk for today for me was the “Lessons learned from social games” presented by Hugh de Loayza from Zynga Inc. He states that social games are meant for socializing, which is also the viral component. One plays, invitest friends, plays again, gets invited, … And thats different from casual gaming, which is not necessarily a social thing. Business models are mainly based on advertising or micro transactions, whereas the latter just starts in the U.S. Hugh states that this is not the end of possible models, but there will be new ones. An interesting thing he pointed out is that he came into Zynga as “the game guy” in a company full of “web 2.0 guys”, which was a clash of culture. They had to work on the integration of game mechanics and social interaction. The focus of social games is more on traffic and interactions (installs,invites, gifts, etc.) than actual game play. The benefit is that one can look at and adopt the game mechanics of other social games (so a big part of the innovation is in the interaction and socializing part). There are also some hints for first approaches:
- keep it more casual than casual (kiss),
- build viral mechanics into the game (gifting, competition, crewing like building up groups by invites, notifications, etc.),
- less game, more social,
- use ubiquitous technologies (e.g. flash, php) and
- think reach (which and how many social networks will be reached).
He also mentions how to bring a social game to market. One needs to seeds the game by
- buying installs,
- trading installs with other developers (cross promotion) or
- develop a brand, a social network within a social network based on your game.
Biggest mistakes in social games are
- licenses (people seem to be not interested),
- linking to a destination site (breaks the viral loop),
- converting existing games,
- overthinking everything (just try it!) and
- widgets (they just don’t work, e.g. they break the viral loop).
Lately it was getting more and more challenging to hear a song you want online. YouTube sorts out based on Geo-IP, samples in online stores get shorter if even there. But I was pointed to a straightforward portal: Grooveshark. You just searcfh for the song you’d like to hear, press play and there you are. If you want to listen to multiple songs, there’s a queue usable without registration. Nice!
While writing a scientific paper on tag recommendation I checked – just out of curiosity – the share of images tagged by their uploaders on Flickr. I found out that 4 out of five images are untagged and that less than 15% of images have 2 or more tags.
My method and detailed results: In general one would need a random sample for such an investigation, but a truly random sample is hard to obtain without access to the data base. Therefore I just grabbed 20,004 images from the RSS feed for recent uploads and counted the number of tagged images. Easy enough I also computed the confidence interval:
- In my sample 3,650 images were tagged with at least one tag, that makes p1=18.25%
- With alpha=0.99 p1 is in [16.84, 19.66].
- That leaves more than 4 out of 5 images untagged.
- Also in my sample 2,628 images were tagged with at least two tags, that makes p2=13,14%
- With alpha=0.99 p2 is in [11.9, 14.37].
- That means that less than 15% of the images images have more than one tag.