I recently met with Eurekster CEO Steven Marder for an update on swicki, the company’s community-influenced search service. Rather than the chewing through the worldwide index and link structures, swicki combines several elements to create more finely tuned search results for online communities.
I recently met with Eurekster CEO Steven Marder for an update on swicki, the company’s community-influenced search service. Rather than the chewing through the worldwide index and link structures, swicki combines several elements to create more finely tuned search results for online communities. Swickis combine Web crawling with filters defined by site owners and algorithms that analyze user behavior (keywords and pages accessed) anonymously and automatically, re-ranking results based on the community's search actions. Search parameters can be set to include or exclude sites to fine tune relevance or eliminate/censor unwanted URLs. Search results can include images—initially from Ask Image search feed, PicSearch and user sites such as Flickr—which can be ranked and commented on by publishers and users of the Swicki sites, and can show up in a swicki multimedia BuzzCloud (at right). Marder said that swickis and BuzzClouds will add video in the near future. So far, nearly 23,000 swickis, primarily in English, have been created, Marder said. He expects the number of swickis to exceed 100,000 in the next year, with help of the SwickiADZ program, which allows publishers to generate revenue. "The quality and usage of swickis will increase dramatically to get us to 100 million plus searches per month worldwide," Marder said. "Right now, our network processes approximately 12 million searches per month." In addition, Eurekster works with online publishers such as Forbes and Popular Science to deliver community search. Eurekster shares ad revenue with swicki publishers, who currently can select up to three advertising programs--CPC and CPA-based text, image and widget-based ads--to appear on results pages. In addition, Eurekster has a preferred placement program for purchasing pay-per-click sponsored listings on swicki results pages.
Next steps for Eurekster’s swicki platform is adding a reputation system, similar to how eBay manages reputation sellers and buyers, for contributors and moderators of swicki search engines. This feature will help elicit more explicit social data that can be baked into the search results, Marder said.