Search neutrality is a principle that search engines should have no editorial policies other than that their results be comprehensive, impartial and based solely on relevance. This means that when a user types in a search engine query, the engine should return the most relevant results found in the provider's domain (those sites which the engine has knowledge of), without manipulating the order of the results (except to rank them by relevance), excluding results, or in any other way manipulating the results to a certain bias.
Search neutrality is related to network neutrality in that they both aim to keep any one organization from limiting or altering a user's access to services on the Internet. Search neutrality aims to keep the organic search results (results returned because of their relevance to the search terms, as opposed to results sponsored by advertising) of a search engine free from any manipulation, while network neutrality aims to keep those who provide and govern access to the Internet from limiting the availability of resources to access any given content.
Background
The term "search neutrality" in context of the internet appears as early as March 2009 in an academic paper by the Polish-American mathematician Andrew Odlyzko titled, "Network Neutrality, Search Neutrality, and the Never-ending Conflict between Efficiency and Fairness in Markets". In this paper, Odlykzo predicts that if net neutrality were to be accepted as a legal or regulatory principle, then the questions surrounding search neutrality would be the next controversies. Indeed, in December 2009 the New York Times published an opinion letter by Foundem co-founder and lead complainant in an anti-trust complaint against Google, Adam Raff, which likely brought the term to the broader public. According to Raff in his opinion letter, search neutrality ought to be "the principle that search engines should have no editorial policies other than that their results be comprehensive, impartial and based solely on relevance". On October 11, 2009, Adam and his wife Shivaun launched SearchNeutrality.org, an initiative dedicated to promoting investigations against Google's search engine practices. There, the Raffs note that they chose to frame their issue with Google as "search neutrality" in order to benefit from the focus and interest on net neutrality.
In contrast to net neutrality, answers to such questions, as "what is search neutrality?" or "what are appropriate legislative or regulatory principles to protect search neutrality?", appear to have less consensus. The idea that neutrality means equal treatment, regardless of the content, comes from debates on net neutrality. Neutrality in search is complicated by the fact that search engines, by design and in implementation, are not intended to be neutral or impartial. Rather, search engines and other information retrieval applications are designed to collect and store information (indexing), receive a query from a user, search for and filter relevant information based on that query (searching/filtering), and then present the user with only a subset of those results, which are ranked from most relevant to least relevant (ranking). "Relevance" is a form of bias used to favor some results and rank those favored results. Relevance is defined in the search engine so that a user is satisfied with the results and is therefore subject to the user's preferences. And because relevance is so subjective, putting search neutrality into practice has been so contentious.
Search neutrality became a concern after search engines, most notably Google, were accused of search bias by other companies. Competitors and companies claim search engines systematically favor some sites (and some kind of sites) over others in their lists of results, disrupting the objective results users believe they are getting.
The call for search neutrality goes beyond traditional search engines. Sites like Amazon.com and Facebook are also accused of skewing results. Amazon's search results are influenced by companies that pay to rank higher in their search results while Facebook filters their newsfeed lists to conduct social experiments.