Fail fast, for sure. Give yourself one year to prove it. If you can't prove it in a year, move on. There are plenty of other interesting problems to solve.
20 karma · joined January 31, 2008
Some key differences between what we're doing and Digg, Newsvine:
-news networks --> everything starts with topical networks that members create and join and have full control of
-members can feed in news from any number of sources into their news networks, not just rely on user submissions. IN fact, upon entering some topics (like keywords), we go crawl the web and suggest sources the might want to include.
-today, all news networks on socialmedian are public -- anyone can create and join them. soon, we'll also layer on private networks
-Everything on socialmedian revolves around the member's personalized feed on their homepage. Our algo offers up a personalized view on the news unique to each user based on their interests. We'll also be layering on some unique types of filters (e.g. know what certain types of people are reading)
more on the way :) it's early. only been at it 2 months
Join 3-4 news networks, create 1, and then check out your homepage. Then give us some feedback as to how to make this work for you.
First, let me say that this is ALPHA in every way -- there's very little polish and we've spent 0 time on messaging, faq's, about files, etc. yet. We've only been at this for a few weeks in total.
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Our site basically asks (and is attempting to answer) a big question: What if, instead of just the media companies filtering the news, we could collectively filter the news for each other? Imagine, for instance, if you could know on any given day what articles just your most trusted friends or colleagues are finding important. Or, if you were able to know what every person who has your job title is finding interesting. Or, if you could know what thousands of people from all around the world are finding important on a very specific topic. That’s what we’re after here at social|median.
Our thesis is:
a. Yes, there is a lot of great content out there and the Internet is making content creation and distribution easier and easier.
b. But people need help wading through all that great content and discovering just the news and information that is most relevant to them.
c. A potentially powerful way to help people get a personalized view of news and information would be through collaborative filtering by people with common interests.
At the highest level, what we are trying to do here is to present people with the most relevant personalized news from any source. There’s a ton of content out there (and more being created every day) and as the noise level increases, people need help discovering just the most important stuff to them. That follows whether you are interested in broad topics like Tech News, or Politics, or more specific topics like Rock Band (the game), or android, or modern interior design, etc. Typical RSS readers and news aggregators lack an intelligence layer to cut through the noise and serve up what matters most to the individual based on their own unique “information DNA”
(It’s worth noting that part of our inspiration for this service came when one of our founders was on the treadmill at the gym one day and observing that all 50 people there were watching the same 30 minutes package of CNN Headline News, while all 50 of them most likely have very different interests — it hit him that at some point in the future we should be able to get more of just the news relevant to our unique interests — so we started to think about how we might step our way towards that).
As noted, our thesis is that a way to solve this problem is to utilize collaborative filtering to help people with similar interests identify/discover what to read/view. (that's not all that new). The new part is the notion that on any specific topic (down to the topic level), there are a set of people who can help other people discover what matters, from any number of sources....SORT OF LIKE HACKER NEWS FOR AN INFINITE NUMBER OF TOPICS/GROUPS OF PEOPLE.
On socialmedian, a group of people who share interest in a common topic or set of related topics form a “News Network” -- which enables them to collectively discover and identify to each other relevant stories. Wiki-like, social|median’s members can create and join News Networks on any topic they desire. Again, wiki-like, in each News Network, the members decide everything. They pick which topics to include in a News Network and what sources to get news from. Finally, within a News Network, members identify interesting stories to each other by “clipping them.”
So far, our 2000 alpha users have created more than 600 "News Networks"
Our Product Model: Ship fast and iterate faster, following user feedback. We launched the first early alpha version of our website in March after just 3 weeks of development and have committed ourselves to rapidly add new features regularly (currently 3 times per week) based on user feedback. We wont always get it right but we are committed to trying, listening, and learning.
Please submit feedback using the links on the site.
Thanks!
We've opened up 100 invites using this code today.