Search: from tool to content platform

There is a shift happening in search. In my last post, I tried to make the case that web content is becoming more decentralized, with aggregators (RSS readers, search engines, and social networks) playing an increasingly large role for the way that we absorb information online, and that this tendency presents new opportunities for the design of information. With this decentralization (or centralization, depending on your perspective), search engines themselves are changing from navigational tools to content platforms.

Many think that the biggest competition to search is presented by social networks. Mark Pincus of Zynga talks about a public and a private web, with an unauthenticated mode addressing a general public, and an authenticated mode based on individual social networks. Websites offering a password-protected, personalized experience will increasingly need to take advantage of social networks to incentivize people to sign up, either by creating new social networks or leveraging existing ones. This evolution will simply serve to further integrate content providers and social platforms, making it easier to recommend and share content with one’s followers or friends. Here, we ourselves are becoming curators for our social network—an authority regarding content that others might find relevant and interesting.

This makes search less important than it used to be, though it still remains the primary authority for the public web. Of course, there are many authoritative and reputable brands among online content providers, from traditional media companies that have translated their offering online, to new content providers that have emerged in the online space, to individual bloggers. The sheer breadth of available content explains why we are increasingly looking towards our social networks to help us regularly digest information. But it also explains why search engines have established themselves as premier authorities for content in the realm of the public web.

Clay Shirk recently wrote a piece about what he calls algorithmic authority: “Authority thus performs a dual function; looking to authorities is a way of increasing the likelihood of being right, and of reducing the penalty for being wrong.  […] Algorithmic authority is the decision to regard as authoritative an unmanaged process of extracting value from diverse, untrustworthy sources, without any human standing beside the result saying ‘Trust this because you trust me.’”

The first company we think of as having established and capitalized on the notion of algorithmic authority is Google. Google has built its reputation on a perception of neutrality via its PageRank algorithm, which has succeeded phenomenally in providing relevant search results. So while individual recommendations are important relative to the private web, the algorithm has become an equivalent authority for the public web.

Seen in this light, it is no stretch to think of search as moving from a mere navigational tool, to becoming an editorialized space for surfacing content, within the framework of the search algorithm. Search engines are in the unique position to feature specific topics that aggregate a multitude of sources, lending it potentially higher credibility than any single source could assume.

Google News was one of the first attempts at creating an editorialized space by leveraging its search algorithm. A more recent development is Google’s Living Stories, which combines news articles from various sources, over time, to form complete coverage on a particular topic. As Living Stories shows, editorialized search is primarily about aggregation and combination, rather than the decontextualization (the traditional search model).

Microsoft’s Bing features particular pieces of content related to each-other through search queries. The daily image on its homepage links to various search queries corresponding to relevant content types (web sites, videos, images, maps, etc.), showing for example the location of the photograph on a map, in addition to a Wikipedia article and an image search on the subject. Bing’s Visual Search involves linking objects, related by object type and various attributes, to specific search queries, in essence allowing their comparison through quantitative visualization. What makes this approach novel is that it provides an editorialized framework for corresponding information from various sources, via the search algorithm.

While these are all early steps, they compellingly demonstrate the potential of search as a content platform, and point to the future of search engines as providing an alternative, authoritative source to individual recommendations.

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