Hey All. I feel that is has been a while since I have written a blog post that really gave insight and was engaging. Lately I have been doing a lot of regurgitation and PodcampNYC'ing. Those of you who know me know that my catch phrase is, "I am so busy"
I want to tell you more about Collarity (as promised in post in this post http://amediacirc.us/2006/11/13/collarity/).
First off, I want to let you know that when I posted this I got a response from someone over at Collarity. Not only does this signal a company that gets new marketing but, it shows me they care.
I engaged him to help me understand his product with a number of questions. In light of a recent indecent in which a personal email was exposed I won’t mention any names, nor will I copy and paste from the email. What I will do is share some of the highlights about Collarity from their perspective.
I have played with the product and it is super cool and very functional. I will however reserve further judgment for now.
Disclaimer: This is an intentional plug for a company that is promoting and educating people about their product the right way. This fact alone makes me love it! The below bullets are paraphrases and not direct quotes (I sure hope I get this right :) )
- Collarity does not intend to be a destination for consumers. It is a service for publishers to
- Help them make older content discoverable
- Enable members of a sites community to help make content findable to themselves and others (folksonomy)
- “Diggs” or “Votes” are performed by way of click to help preserve the integrity of the wisdom of crowds (that last bit about integrity was my spin, I think it makes sense though).
- Collarity focuses on what they call “implicit social search” (see excerpt from Wikipedia below) mechanics (fancy!)
- The audience need do what they always have done and let the algorithm do the taxonomy, categorization and create searchable content
These bullets were all response to my inquiries. I am sure that Collarity has a lot more to say about themselves and I am giving an official invite to them (I have never done this before) to take over A Media Circus for a post.
You got it folks; I am inviting Collarity to write a post for me that will educate you about their product (and hopefully about concepts relating to social search in general as well).
Let’s see if they are up for the challenge :)
To be an unfair and impartial blogger I am also inviting any other social search engine to submit an article. It can be a competitive piece that challenges Collarity or something completely different however, only Collarity’s piece will not have to undergo the rigorous Media Circus vetting process!
Tags: social search, collarity, implicit social networks, Wikipedia, A media circus, Digg, Folksonomy, PodcampNYC, New Marketing, Wisdom Of Crowds, implicit social search mechanics, A Media Circus Challenge
Social network search engines are a class of search engines that use social networks to organize, prioritize, or filter search results.
There are two subclasses of social network search engines: those that use explicit social networks, and those that use implicit social networks.
Explicit social network search engines allow people to find each other according to explicitly stated social relationships such as XFN social relationships. For example, XHTML Friends Network allows people to share their relationships on their own sites, thus forming a decentralized/distributed online social network, in contrast to centralized social network services listed in the previous section.
Implicit social network search engines allow people to filter search results based upon classes of social networks they trust, such as a shared political viewpoint. This type of social network search engine mines the web to infer the topology of online social networks. For example, the NewsTrove search engine infers social networks from content - sites, blogs, pods, and feeds - by examining (among other things) subject matter, link relationships, and grammatical features to infer social networks. The user may then employ the social networks as filters to their search results.