On Facebook, Friendfeed
One of the more difficult decisions working on the latest Valentine's Day version of Semantic Gifts was the removal of Facebook and FriendFeed as source options for gift recommendations. In my Christmas edition I had the ability to use Facebook, FriendFeed, Twitter, or an open Http:// string. For the Valentine's edition I've decided to use only Twitter. Though my extreme minimalism was the antagonist for the removal of each, they all had their own list of pros and cons.
I get many things from Facebook integration. Name, sex, location, friend ratios, and occasionally interests, hobbies, movies, etc. But as the API stands I can't get the text of the recipient's comments, posts, or historical status updates. Technically speaking I have named entities to extract but I don't have natural language to process, and Semantic Gifts is very much an NLP driven app. The first response from everyone is "Aren't you cutting out a wide swath of your potential userbase?" and it's true. There are lots of people who use Facebook who aren't yet on Twitter. But without free writing samples I can't demonstrate what Semantic Gifts can do, and there's nothing I can say based on a list of interests that you couldn't figure out on your own. It's actually worse than that, because a given user will assume I can get everything that person has ever said on Facebook, which isn't possible, and will thus be doubly disappointed.
I'd add that in conjunction with other sources Facebook is awesome though, and is slotted to return for the next iteration of Semantic Gifts "Classic". The hard data used to seed the algorithm is instead coming from a Girls' page this time around. Each has advantages and disadvantages.
Twitter is the 500 lb gorilla. I loathe the idea of Semantic Gifts being categorized as a "Twitter app", but in general it gives us the data we need to make Semantic Gifts do what it does. And it is pretty awesome. Sooner or later everyone is going to catch on that combining microblog pithiness with modern concept mining you can extract some pretty good scores without waiting for ratings or search strings, and everyone will do recommendation this way. Twitter is good, and would be better if everyone used it the same way...
Which is what makes FriendFeed much harder to exclude from this round. On the one hand it seems much more heterogeneous - you have all kinds of different primary sources. But when you look closer at the text that comes back... the ubiquity of opinion expression that is our best recommendation fuel... you find topic introduction and discussion in a wonderfully contextualized way. I am coming around to the idea that for our type of recommendation to truly take over it will be running against lifestreams, not microblogs.
In the meantime the traffic numbers haven't justified the real estate for FriendFeed in the Valentine's version. I expect it to stay on for the classic edition and potentially become my primary source in the future (I am looking forward to that).
A little design commentary is necessary to put the cuts in context... the primary driver to remove anything at all is a strong (possibly relentless) drive for minimalism in the interface. The longer I do this the more strongly I believe each element has to justify its continued presence every major release.
Which is easy for me to preach about because Semantic Gifts is a casual app with a nascent technology in a not quite emerging market, but the exercise of touching each item on your site with a skeptical eye and forcing yourself to justify not commenting it out is an approach that I think should be applied to any application.
I get many things from Facebook integration. Name, sex, location, friend ratios, and occasionally interests, hobbies, movies, etc. But as the API stands I can't get the text of the recipient's comments, posts, or historical status updates. Technically speaking I have named entities to extract but I don't have natural language to process, and Semantic Gifts is very much an NLP driven app. The first response from everyone is "Aren't you cutting out a wide swath of your potential userbase?" and it's true. There are lots of people who use Facebook who aren't yet on Twitter. But without free writing samples I can't demonstrate what Semantic Gifts can do, and there's nothing I can say based on a list of interests that you couldn't figure out on your own. It's actually worse than that, because a given user will assume I can get everything that person has ever said on Facebook, which isn't possible, and will thus be doubly disappointed.
I'd add that in conjunction with other sources Facebook is awesome though, and is slotted to return for the next iteration of Semantic Gifts "Classic". The hard data used to seed the algorithm is instead coming from a Girls' page this time around. Each has advantages and disadvantages.
Twitter is the 500 lb gorilla. I loathe the idea of Semantic Gifts being categorized as a "Twitter app", but in general it gives us the data we need to make Semantic Gifts do what it does. And it is pretty awesome. Sooner or later everyone is going to catch on that combining microblog pithiness with modern concept mining you can extract some pretty good scores without waiting for ratings or search strings, and everyone will do recommendation this way. Twitter is good, and would be better if everyone used it the same way...
Which is what makes FriendFeed much harder to exclude from this round. On the one hand it seems much more heterogeneous - you have all kinds of different primary sources. But when you look closer at the text that comes back... the ubiquity of opinion expression that is our best recommendation fuel... you find topic introduction and discussion in a wonderfully contextualized way. I am coming around to the idea that for our type of recommendation to truly take over it will be running against lifestreams, not microblogs.
In the meantime the traffic numbers haven't justified the real estate for FriendFeed in the Valentine's version. I expect it to stay on for the classic edition and potentially become my primary source in the future (I am looking forward to that).
A little design commentary is necessary to put the cuts in context... the primary driver to remove anything at all is a strong (possibly relentless) drive for minimalism in the interface. The longer I do this the more strongly I believe each element has to justify its continued presence every major release.
Which is easy for me to preach about because Semantic Gifts is a casual app with a nascent technology in a not quite emerging market, but the exercise of touching each item on your site with a skeptical eye and forcing yourself to justify not commenting it out is an approach that I think should be applied to any application.
posted by A at
3:35 PM
0 Comments:
Post a Comment
<< Home