Tags: seo, social media, social search, social networking, SES NYC, search

Here’s a beakdown of this session…

Chris Sherman (host) – Search Engine Land

• What is social search?
• • Internet way-finding tools informed by human judgment
  • Egregiously uninformed – people have influence on results we see
• Meta tags in 1996 were a failure (spam), but now, in different form are coming back (tagging blog posts, Digg submissions, etc..)
• Search engines reflect human bias (programmer choices)
• Algorithms follow click paths, popular URLs, etc.. so they can modify the algorithms appropriately
• Buzz around social search
• • Algorithmic search has plateau – innovation is harder than before
  • Humans are better than computers (social search defined by humans), image search is good example of this
  • Leveraging the work of volunteers (social search efforts)
• Types of Social Search
• • Shared bookmarks & web pages – del.icio.us, Shadows, MyWeb, Furl, Diigo
  • Tag engines (blogs & RSS) – Technorati, Bloglines
  • Collaborative directories – ODP, Prefound, Zimbio, Wikipedia
  • Personalized verticals – Google custom search, Eurekster, Rollyo, Trexy
  • Collaborative harvesters (work on news, article submission, vote on worth) – Digg, Netscape, Reddit, Popurls.com (aggregates all together)
  • Social Q&A sites – Google Answers, Yahoo Answers, Answerbag
  • • Yahoo has even applied it’s algorithmic knowledge to Yahoo answers
• Problems
• • Scale and scope issues
  • Tagging issues
  • • Ambiguity of language
    • Idiots
    • Laziness – people don’t take the effort to tag properly
    • Lack of controlled vocabulary
  • Spammers – because social search is new, don’t have safeguards in place yet
• What works
• • Combo of algorithmic and people mediated search, blend the two together
  • Trust networks – like link trust algorithms emplore
  • Increased personalization and user control over result filtering – humans can filter their own results and sources
  • Near future – will work best for photos, music, video, etc… what the search engines can’t “see”.  This is where the algorithm falters and we need the human element to describe these kind of things

Seth Godin – Founder of Squidoo

• Uses example on squidoo – Martha Stewart search in google – 3^rd result is a squidoo portal about Martha Stewart cookies
• Serves as a buffer page – gets you from search engine to this page and then to proper page – put together by a “human”.  A post computer filter
• Another example – laptop bags – shows up #1 squidoo lens from a user.  Constantly updated by user, like a blog, about laptop bags.  She acts as a “filter” that cuts down the results from the search engines – one’s she finds relevant
• If you have a blog, your relevant content that you think is best gets squashed.  On a squidoo page, you can put your best stuff on top, along with what you are all about.  People can get a good glimpse about what your blog is all about as a whole prior to someone getting to know your blog

Apostolos Gerasoulis– Head of search at ask.com

• Feels that social search is the future of search
• Algorithmic search has peaked

Tomi Poutanen – Yahoo! answers

• Flickr – get more human results than algorithmic image search, can be much more engaging
• • Flickr geocoded, geotagged – have pics on yahoo maps, with descriptions
• Del.icio.us – social bookmarking, enables people to share pages of interest with their network – search tags with “tag:search phrase”
• Yahoo! Answers – ask a question, and the community as a whole answers the question