In today’s online world, personalization is increasingly making or breaking companies. The companies that win are the ones making personalization a key company value – not just a feature.
What’s really interesting here is that this is the first sign of Twitter getting serious about building its own interest graph, as if you’d ever get tired of all this “graph” talk, right? But this is the social network’s first big move that shows it following in the footsteps of Facebook, as the more personal info they collect on your interests and activity on their platform, the more info there is to feed targeted advertising and tweets.
TechCrunch, Twitter Wants An Interest Graph: Now Tracking Your Browsing To Make Follow Suggestions, May 18, 2012
Although Thirst is starting out on the Twitter platform, the company is really more about natural language processing technology. The Twitter iPad app is more of a proof of concept around whether its NLP processor works well. Verma says that it’s really difficult to keep up with information shared through Twitter and there has to be a better way of surfacing the most important news. Thirst uses a custom natural language processor to pick out the most important stories around different keywords or subjects like ‘gay marriage’ (because of this past week’s big announcement from President Barack Obama in support of it).
Techcrunch, Thirst Aims To Slake Your Hunger For Relevant Twitter Content, May 16, 2012
I certainly send the Twitter engine enough signals — tweets, retweets, follows, followers, and location data — to help determine what is important to me. So far, though, I have to believe that Twitter’s Discovery engine has mistaken me for another user.
, Twitter’s strange Discovery engine, May 15, 2012
Ongo to close doors
We believe in Ongo’s unique approach, blending aggregated news sources with the curation only a professional editorial staff can provide. Unfortunately, we may be too far ahead of the general market’s readiness to adopt such a solution, and business realities leave us no option but to close our doors. (Ongo announcement to subscribers)
But it’s important to note that Ongo drew skepticism from media watchers from the start. Its business model rested on the belief that people would value an ad-free, curated experience enough to pay for it, despite both the availability of the (mostly) free web and other free apps like Flipboard.
Facebook will continue testing new formats in search of one that sends lots of referral traffic, but to high-quality articles. News reader developers should hold tight, talk to their Facebook reps about how changes are hurting user counts, and hope an optimal version of “recently read articles” emerges soon. But just because there was massive organic referral traffic to be had until now is no guarantee it will return.
TechCrunch, Decline Of Reader Apps Likely Due To News Feed Changes, Shows Facebook Controls The Traffic Faucet, May 7, 2012
The likes of Amazon and Netflix invest millions of dollars on designing the ”perfect” algorithm to predict what you’re likely to want next. Recommendation algorithms are hugely important within the e-commerce space – the history of your actions on the site will inform what the site suggests to you in future.
Action: You probably don’t have millions to invest in developing recommendation engines or fancy formulas that tell your customer what they should do next. What you can do is look a little bit wider than mass personalisation.
Relevance - The Key to Content Discovery by Scott Gray, May 2, 2012
Actually Relevancer provides “recommendation engines” and “fancy formulas” via a white label service for any website and it doesn’t cost millions.
U.S. Patent No. 8,171,128 — “Communicating a newsfeed of media content based on a member’s interactions in a social network environment” – Filed on August 11, 2006, and granted on May 1, 2012.
Facebook patents the News Feed, via ZDNet.
The question then becomes: will they use the patent offensively or defensively against other social networks that display news feeds in much the same way (eg., Twitter, LinkedIn, Tumblr, etc.).
Via ZDNet:
Reading the patent more closely, you’ll see Facebook discusses how to let users see certain status updates, pictures, links to videos, and even actions friends take. The social networking giant describes keeping a profile of each person on the social network in a database, identifying relationships between said users, generating “stories” based on the connections, and then creating a News Feed for each user.
Last but certainly not least, Facebook watches what actions the viewer takes in response to the stories (such as Liking, Sharing, or commenting), and then uses that information to serve more stories. It’s also noted that content can come from outside the social network and that users can change preference settings to filter in or out what stories they see.
(via futurejournalismproject)
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Twitter’s big problem: It still needs better filters
Figuring out a user’s broader “interest graph” is no easy task at the best of times, especially when the only thing Twitter has to go on is 140 characters of text and perhaps an image now and then. Recommendation services are a little like voice-recognition, in that no one notices when you get it right but everyone hates you when you get it wrong. But more than anything else, that is what Twitter has to figure out — and soon, before someone else does it better.
The book goes into great detail on how current copyright laws are stifling technological and creative progress, as well as the freedom of private communication and due process. It also lays out evidence from Norway and Sweden to show that artists can still make money in a world where their works can be copied freely, by shifting to other revenue sources. Perhaps the detailed argument will help change the minds of some of those German intellectuals that have been reportedly turning against the party recently.
