From Semantic Search to Social Search using Mobile Devices

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Starting about 1970, the Internet was built on a base of text; most early communications between computers were text messages or documents. Then, in 1992, Tim Berners-Lee invented the World Wide Web, which used books with pages as its main metaphor. Until recently, search engines have gone looking for words, or combinations of words, in order to deliver relevant “documents” to the searcher. We can refer to this approach as “semantic search.”

While semantic search is still heavily used, with the rise of social networking and use of mobile phones, a new approach to finding things is emerging, called “social search.” Here the goal is not to find a collection of Web pages or documents, but to locate the right person who can answer the user’s needs. According to a recent paper by Damon Horowitz of Aardvark and Sepandar Kamvar of Stanford University, a better metaphor for searching is “the village” composed of people with many different skills and kinds of knowledge. They say:

“In a village, knowledge dissemination is achieved socially — information is passed from person to person, and the retrieval task consists of finding the right person, rather than the right document, to answer your question.”

Using a village metaphor has implications for the design of a mobile social search engine such as Aardvark. Instead of using keywords to search, is more appropriate to use natural language to ask questions. And, the ranking algorithm used by a social search engine will be different than that for a semantic search engine. For example, Aardvark uses three main factors in ranking search results:

  • Topic Expertise – does a person answering the question know what they’re talking about?
  • Connectedness – how well is the person answering matched to the person who is asking the question?
  • Availability – because the searcher may have additional questions, it may be important that the person who is answering is available online at the time the questions asked.

The implications of social search are profound for the learning industry. For example, Google is still mostly based on semantic search (although there have been attempts to increase its social content) while Facebook and Twitter can be used to query friends at a moment’s notice and get back useful results very quickly. In January 2010, the Web traffic analysis firm Experian Hitwise reported that social networking sites have, for the first time, passed search sites in terms of network traffic. In February of this year, Google responded with an improved social search engine, showing how seriously they are taking this threat. Then, in April they bought Aardvark. (However, Google recently announced it would be discontinuing the service.)

There is a danger in overreliance on social search engines to find everything we are looking for. Because our close friends often have similar knowledge, tastes and lifestyles, we may find all the search results looking the same. Sometimes we are looking for recommendations from those we know and trust, but at other times, we are looking for diversity in search results. In other words, both kinds of searches are necessary.

If you want to try social search on your mobile phone, here are a few choices:

Let me know if you find more mobile social search engines, and tell me what you think of them.

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Gary Woodill is a senior analyst with Float, as well as CEO of i5 Research. Gary conducts research and market analyses, as well as assessments and forecasting for emerging technologies. Gary is the co-editor of "Mastering Mobile Learning," author of “The Mobile Learning Edge,” and the co-author of “Training and Collaboration with Virtual Worlds.” He also presents at conferences and is the author of numerous articles and research reports on emerging learning technologies. Gary holds a doctor of education degree from the University of Toronto.

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On September 14, 2011
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