Group items tagged

The Wisdom of Crowds

growing popularity of social software and Web 2.0

Social computing begins with the observation that humans — and human behavior — are profoundly social

social information provides a basis for inferences, planning, and coordinating activity

The premise of social computing is that it is possible to design digital systems that support useful functionality by making socially produced information available to their users

Google's page rank algorithms which orders search results based on the number of pages that (recursively) point to them

Social computing can be defined as follows: Social Computing" refers to systems that support the gathering, representation, processing, use, and dissemination of information that is distributed across social collectivities such as teams, communities,organizations, and markets. Moreover, the information is not "anonymous" but is significant precisely because it is linked to people, who are in turn linked to other people.

Web 2.0 Main article: Web 2.0 A generation of internet applications was developed implementing aspects of social computing developed in the early 21st century.

Enterprise social software Main article: Enterprise social software Of particular interest in the realm of social computing is social software for enterprise. Sometimes referred to as "Enterprise 2.0",[2] a term derived from Web 2.0, this generally refers to the use of social computing in corporate intranets and in other medium- and large-scale business environments.

Collaborative filtering Main article: Collaborative filtering Collaborative filtering is the method of making automatic predictions (filtering) about the interests of a user by collecting taste information from many users (collaborating). Recommender systems often use it as a "social approach" in order to obtain music, movie, product, web site etc. recommendations.

Concerns Risk of spam. Because users can directly add results to a social search engine there is a risk that some users could insert search spam directly into the search engine. Elimination or prevention of this spam would require the ability to detect the validity of a user's' contribution, such as whether it agrees with other trusted users. "The Long Tail" of search is a concept that there are so many unique searches conducted that most searches, while valid, are performed very infrequently. A search engine that relied on users filling in all the searches would be at a disadvantage to one that used machines to crawl and index the entire web.

Benefits To date social search engines have not demonstrated measurably improved search results over algorithmic search engines. However, there are potential benefits deriving from the human input qualities of social search. Reduced impact of link spam by relying less on link structure of web pages. Increased relevance because each result has been selected by users. Leverage a network of trusted individuals by providing an indication of whether they thought a particular result was good or bad. The introduction of 'human judgement' suggests that each web page has been viewed and endorsed by one or more people, and they have concluded it is relevant and worthy of being shared with others using human techniques that go beyond the computer's current ability to analyze a web page. Web pages are considered to be relevant from the reader's perspective, rather than the author who desires their content to be viewed, or the web master as they create links. More current results. Because a social search engine is constantly getting feedback it is potentially able to display results that are more current or in context with changing information.

Social search or a social search engine is a type of web search method that determines the relevance of search results by considering the interactions or contributions of users

he concept of social ranking can be considered to derive from Google's PageRank algorithm,[citation needed] which assigns importance to web pages based on analysis of the link structure of the web, because PageRank is relying on the collective judgment of webmasters linking to other content on the web. Links, in essence, are positive votes by the webmaster community for their favorite sites.