Act of retrieving and searching on a social searching engine
Social search is a behavior of retrieving and searching on a social searching engine that mainly searches user-generated content such as news, videos and images related search queries on social media like Facebook, LinkedIn, Twitter, Instagram and Flickr.[1] It is an enhanced version of web search that combines traditional algorithms. The idea behind social search is that instead of ranking search results purely based on semantic relevance between a query and the results, a social search system also takes into account social relationships between the results and the searcher.[2][3][4] The social relationships could be in various forms. For example, in LinkedIn people search engine, the social relationships include social connections between searcher and each result, whether or not they are in the same industries, work for the same companies, belong the same social groups, and go the same schools, etc.[2][5]
Social search may not be demonstrably better than algorithm-driven search.[6] In the algorithmic ranking model that search engines used in the past, relevance of a site is determined after analyzing the text and content on the page and link structure of the document. In contrast, search results with social search highlight content that was created or touched by other users who are in the Social Graph of the person conducting a search. It is a personalized search technology with online community filtering to produce highly personalized results.[7] Social search takes many forms, ranging from simple shared bookmarks or tagging of content with descriptive labels to more sophisticated approaches that combine human intelligence with computer algorithms. Depending on the feature-set of a particular search engine, these results may then be saved and added to community search results, further improving the relevance of results for future searches of that keyword. The principle behind social search is that human network oriented results would be more meaningful and relevant for the user, instead of computer algorithms deciding the results for specific queries.[8][9][10][11]
^"SocialSeeking – Social Search Engine". Archived from the original on 2016-04-28. Retrieved 2015-12-01.
^"What is Social Search? - Definition from Techopedia". Techopedia.com. 30 September 2014.
^"What is social search engine? - Definition from WhatIs.com". WhatIs.com.
^Ha-Thuc, Viet; Sinha, Shakti (2016-05-15). "Learning to Rank Personalized Search Results in Professional Networks". Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval. Vol. 2016. pp. 461–462. arXiv:1605.04624. Bibcode:2016arXiv160504624H. doi:10.1145/2911451.2927018. ISBN 9781450340694. S2CID 14924141. {{cite book}}: |journal= ignored (help)
^Lyngbo, Trond (January 2013). "What Is Social Search?". Archived from the original on 2016-03-30. Retrieved 2015-12-01.
^Hsieh, Hsun-Ping (August 2015). "I See You". Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval. Sigir '15. pp. 839–842. doi:10.1145/2766462.2767767. ISBN 9781450336215. S2CID 1109587.
^Chi, Ed H. Information Seeking Can Be Social, Computer, vol. 42, no. 3, pp. 42-46, Mar. 2009 Archived 2012-10-03 at the Wayback Machine, doi:10.1109/MC.2009.87
^A Taxonomy of Social Search Approaches Archived 2008-10-05 at the Wayback Machine, Delver company blog, Jul 31, 2008
^Longo, Luca; Dondio, Pierpaolo; Barrett, Stephen (2010). "Enhancing Social Search: A Computational Collective Intelligence Model of Behavioural Traits, Trust and Time". Transactions on Computational Collective Intelligence II. Lecture Notes in Computer Science. Vol. 6450. pp. 46–69. doi:10.1007/978-3-642-17155-0_3. ISBN 978-3-642-17154-3.
^Luca, Longo; Stephen, Barrett; Pierpaolo, Dondio (2009). "Information Foraging Theory as a Form of Collective Intelligence for Social Search". Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems. Lecture Notes in Computer Science. Vol. 5796. pp. 63–74. doi:10.1007/978-3-642-04441-0_5. ISBN 978-3-642-04440-3.
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