173:) developed a web browser plugin "HayStaks". HeyStaks applies social search through collaboration in web search as a way that leads to better search results. The main motivation for HeyStaks to work on this idea is to provide the user with features that search engines didn't provide at that time. For instance, different searches have indicated that about 70% of the time when user search for something, a friend or a coworker have found it already. Also, studies have shown that approximately, 30% of people who use online search, search for something that they have found before. The startup believe that they help avoid these kind of issues by providing a shared and rich search experience through a list of recommendations that get generated based on search results.
287:. Aardvark is a social search engine that is based on the "village paradigm" which is about connecting the user who has a question with friends or friends of friends whom can answer his or her question. In Aadvark, a user ask a question in different ways that mostly involves online ways such as instant messaging, email, web input or other non-online ways such as text message or voice. The Aardvark algorithm forwards the question to someone in the asker extended social network who has the highest probability in knowing the answer to the question. Aadvark was obtained by
444:
properties of these problems share similar structures and, often, similar solutions. Moreover, internal search (e.g., memory search) shows similar characteristics to external search (e.g., spatial foraging), including shared neural mechanisms consistent with a common evolutionary origin across species. For search scenarios, organisms must detect – and climb – noisy, long-range environmental (e.g., temperature, salinity, resource) gradients. Here,
280:
considered a part of Web 2.0 because they use the collective filtering of online communities to elevate particularly interesting or relevant content using tagging. These descriptive tags add to the meta data embedded in Web pages, theoretically improving the results for particular keywords over time. A user will generally see suggested tags for a particular search term, indicating tags that have previously been added.
347:' lets users see popular articles they might want to include in their status updates and comments by entering a search query. The results appear to comprise articles that have been well-shared by other Facebook users, with the most recently published given priority over others. The option certainly makes it easier for users to add links without manually searching their News Feed or resorting to a
365:'. The new Tailored Trends feature, besides showing Twitter trends, will give a short description of each topic. Since trends tend to be abbreviations without context, a description will make it more clear what a trend is about. The new trends experience may also include how many Tweets have been sent and whether a topic is trending up or down.
263:. However, social discovery is not limited to meeting people in real-time, it also leads to sales and revenue for companies via social media. An example of retail would be the addition of social sharing with music, through the iTunes music store. There is a social component to discovering new music Social discovery is at the basis of
250:'s search results in November 2013. Yet Twitter has its own search engine which points out how much value their data has and why they would like to keep it in house. In the end though social search will never be truly comprehensive of the subjects that matter to people unless users opt to be completely public with their information.
73:. 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. The social relationships could be in various forms. For example, in
294:
Potential drawbacks to social search lie in its open structure, as is the case with other tagged databases. As these are trust-based networks, unintentional or malicious misuse of tags in this context can lead to imprecise search results. There are number of social search engines that mainly based on
188:
and Google were already taking into account re-tweets and Likes when providing search results. However, after a search deal with
Twitter ended without renewal, Google began to retool its Social Search. In January 2012, Google released "Search plus Your World", a further development of Social Search.
94:
filtering to produce highly personalized results. 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
384:
However this is not possible unless social media sites decide to work with search engines, which is difficult since everyone would like to be the main toll bridge to the internet. As we continue on, and more articles are referred by social media sites, the main concern becomes what good is a search
275:
A social search engine in an aspect can be thought of as a search engine that provides an answer for a question from another answer by identifying a person in the answer. That can happen by retrieving a user submitted query and determining that the query is related to the question; and provides an
258:
Social discovery is the use of social preferences and personal information to predict what content will be desirable to the user. Technology is used to discover new people and sometimes new experiences shopping, meeting friends or even traveling. The discovery of new people is often in real-time,
279:
Few social search engines depend only on online communities. 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. Social search engines are
380:
works. Semantic search understands much more, including where you are, the time of day, your past history, and many other factors including social connections, and social signals. The first step in order to achieve this will be to teach algorithms to understand the relationship between things.
396:
in which users provide the data they seems appropriate. Since the data used by search engines belongs to the user they should have absolute control over it. The infrastructure required for a search engine is already available in the form of thousands of idle desktops and extensive residential
443:
Besides above engineering explorations, a more fundamental and potential method is to develop social search systems based on the understanding of related neural mechanisms. Search problems scale from individuals to societies, however, recent trends across disciplines indicate that the formal
99:, 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
166:'s methodology. This suggests growing interest in how social groups can influence and potentially enhance the ability of algorithms to find meaningful data for end users. There are also other services like Sentiment that turn search personal by searching within the users' social circles.
85:
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
193:
profiles. The goal was to deliver better, more relevant and personalized search results with this integration. This integration however had some problems in which Google+ still is not wildly adopted or has much usage among many users. Later on, Google was criticized by
198:
for the perceived potential impact of "Search plus Your World" upon web publishers, describing the feature's release to the public as a "bad day for the web", while Google replied that
Twitter refused to allow deep search crawling by Google of Twitter's content. By
77:
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.
230:
still in the beta stages. The goal was to allow users to prioritize results that were popular with their social circle over the general internet. Facebook's Graph search utilized
Facebook's user generated content to target users.
412:
and secure social search. Data privacy protection is defined as the way users can fully control their data and manage its accessibility. The solutions for data privacy include information substitution, attributed based
218:
In
December 2008, Twitter had re-introduced their people search feature. While the interface had since changed significantly, it allows you to search either full names or usernames in a straight-forward search engine.
908:
Smyth, B., Balfe, E., Freyne, J., Briggs, P., Coyle, M., Boydell, O.: Exploiting query repetition and regularity in an adaptive community-based web search engine. User Model. User-Adapt. Interact. 14(5), 383–423
111:
Over the years, there have been different studies, researches and some implementations of Social Search. In 2008, there were a few startup companies that focused on ranking search results according to one's
417:
and identity based broadcast encryption. The data integrity is defined as the protection of data from unauthorized or improper modifications and deletions. The solutions for data integrity are
436:
from observed multimedia data. The solutions are based on how to effectively and efficiently leverage social media and search engine. A potential method is to derive a user-image
215:
profile. In
November 2014 these accusations started to die down because Google's Knowledge Graph started to finally show links to Facebook, Twitter, and other social media sites.
448:
can provide substantial additional benefit by allowing individuals, simply through grouping, to average their imperfect estimates of temporal and spatial cues (the so-called ‘
440:
from social media, and then re-rank image search results by integrating social relevance from the user-image interest graph and visual relevance from general search engines.
207:, the company was encouraging users to switch to Google's social networking site in order to improve search results. One famous example occurred when Google showed a link to
452:’ effect). Due to the investment necessary to obtain personal information, however, this again sets the scene for producers (searchers) to be exploited by others.
773:
558:
Ha-Thuc, Viet; Venkataraman, Ganesh; Rodriguez, Mario; Sinha, Shakti; Sundaram, Senthil; Guo, Lin (2016-02-15). "Personalized
Expertise Search at LinkedIn".
1620:
1061:
948:
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with social search. The goal is a basic search service whose operation is controlled and maintained by the community itself. This would largely work like
1136:
1486:
234:
Although there have been different researches and studies in social search, social media networks have not vested enough interest in working with
404:, it shares several same security concerns as the traditionally centralized case. The security concerns can be classified into three categories:
1342:
1317:
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848:
811:
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for example has taken steps to improve its own individual search functions in order to stray users from external search engines. Even
368:
Google may be falling behind in terms of social search, but in reality they see the potential and importance of this technology with
267:'s profitability, generating ad revenue by targeting the ads to users using the social connections to enhance the commercial appeal.
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721:
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675:
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The feature, which is integrated into Google's regular search as an opt-out feature, pulls references to results from
1242:
770:
615:
Ha-Thuc, Viet; Sinha, Shakti (2016-05-15). "Learning to Rank
Personalized Search Results in Professional Networks".
1699:
1615:
899:
Barry Smyth, Peter Briggs, Maurice Coyle, and
Michael O’Mahony (2009). Google Shared. A Case-Study in Social Search
506:
307:
and Social
Searcher, originally linked to Facebook. Other versions of social engines have been launched, including
1625:
1768:
1684:
530:
1809:
1804:
1709:
1689:
1472:
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Proceedings of the 38th
International ACM SIGIR Conference on Research and Development in Information Retrieval
617:
Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval
284:
792:"Enhancing Social Search: A Computational Collective Intelligence Model of Behavioural Traits, Trust and Time"
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1610:
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481:
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145:
34:
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answer, including the link to the resource, as part of search results that are responsive to the query.
432:
Another issue related to both distributed and centralized search is how to more accurately understand
630:
426:
247:
185:
1300:
Boshrooyeh, Sanaz Taheri (June 2015). "Security and Privacy of Distributed Online Social Networks".
1564:
1559:
496:
445:
373:
300:
184:, the feature was expanded to multiple languages in May 2011. Before the expansion however in 2010
887:
744:
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620:
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501:
401:
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tracking user information to order to provide related search results. Examples of this types are
1178:
Damon Horowitz, Sepandar D. Kamvar(April 1020) The Anatomy of a Large-Scale Social Search Engine
597:
923:
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Chi, Ed H. Information Seeking Can Be Social, Computer, vol. 42, no. 3, pp. 42-46, Mar. 2009
709:
638:
471:
461:
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91:
33:
is a behavior of retrieving and searching on a social searching engine that mainly searches
1212:
833:
Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
324:
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476:
421:, hash chaining and embedded signing key. The solutions for secure social search are
352:
96:
1406:
863:
829:"Information Foraging Theory as a Form of Collective Intelligence for Social Search"
660:
1669:
1584:
731:
405:
393:
369:
227:
149:
113:
87:
42:
38:
1302:
2015 IEEE 35th International Conference on Distributed Computing Systems Workshops
1152:"Bitcovery Brings A Desperately Needed Social Discovery Layer To The iTunes Store"
81:
Social search may not be demonstrably better than algorithm-driven search. In the
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875:
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of the person conducting a search. It is a personalized search technology with
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414:
362:
154:
133:
129:
125:
66:
1704:
1213:"Skip Googling With Facebook's New "Add A Link" Mobile Status Search Engine"
713:
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316:
195:
121:
54:
1089:
Outsmarting Social Media: Profiting in the Age of Friendship Marketing
970:
534:
162:
potentially adding in a voting mechanism to search results similar to
1727:
835:. Lecture Notes in Computer Science. Vol. 5796. pp. 63–74.
798:. Lecture Notes in Computer Science. Vol. 6450. pp. 46–69.
348:
320:
288:
200:
177:
159:
62:
1398:
388:
One development that seeks to redefine search is the combination of
246:
started working with Twitter in order to integrate some tweets into
625:
564:
1464:
1278:
1187:
1358:
Liu, Shaowei (June 2013). "Social-oriented visual image search".
163:
1468:
1422:"Exploration versus exploitation in space, mind, and society"
598:"What is social search engine? - Definition from WhatIs.com"
27:
Act of retrieving and searching on a social searching engine
827:
Luca, Longo; Stephen, Barrett; Pierpaolo, Dondio (2009).
790:
Longo, Luca; Dondio, Pierpaolo; Barrett, Stephen (2010).
990:
988:
796:
Transactions on Computational Collective Intelligence II
1137:"Social Discovery sites' influence on retail expanding"
1385:
Cui, Peng (April 2014). "Social-Sensed Image Search".
971:"Twitter unhappy about Google's social search changes"
922:. March Communications. 10 April 2013. Archived from
580:"What is Social Search? - Definition from Techopedia"
1761:
1718:
1593:
1502:
361:
announced it is replacing its 'Discover' tab with '
211:'s dormant Google+ account rather than the active
1335:Advances in Computing, Communication, and Control
376:. The importance of social media lies within how
180:rolled out its "Social Search"; after a time in
920:"Retweets and Likes influencing search results"
864:New Sites Make It Easier To Spy on Your Friends
283:An implementation of a social search engine is
120:. Companies in the social search space include
1188:"Social Searcher - Social Media Search Engine"
949:"Facebook Announces New Social Search Feature"
876:Social Search Guide: 40+ Social Search Engines
351:query. This new app reduce users' reliance on
1480:
1081:
1079:
8:
1062:"User data will never be competently public"
169:In 2009, a startup project called HeyStaks (
1279:"Towards Distributed Social Search Engines"
103:deciding the results for specific queries.
1487:
1473:
1465:
943:
941:
1445:
1243:"Twitter is killing off its Discover tab"
624:
563:
1387:ACM Transactions on Information Systems
1360:Computer Vision and Image Understanding
1122:"Are Social Discovery Apps Too Creepy?"
522:
1259:. Social Media Today. 28 February 2014
771:A Taxonomy of Social Search Approaches
531:"SocialSeeking – Social Search Engine"
291:in 2010 and abandoned later in 2011.
226:announced a new search engine called
7:
1601:Cross-language information retrieval
1150:Constine, Josh (10 September 2013).
998:. Third Door Media. 18 November 2014
619:. Vol. 2016. pp. 461–462.
553:
551:
866:, Wall Street Journal, May 13. 2008
780:, Delver company blog, Jul 31, 2008
385:engine without the data of users.
339:Confirmed to be in testing, a new
25:
1420:Hills, Thomas T. (January 2015).
1020:. Bub.blicio.us. 23 December 2008
487:Collaborative information seeking
1092:. Que Publishing. pp. 51–.
700:Hsieh, Hsun-Ping (August 2015).
1748:Representational State Transfer
1226:Cselle, Gabor (April 8, 2015).
1018:"Twitter People Search is Back"
708:. Sigir '15. pp. 839–842.
65:. It is an enhanced version of
1580:Natural language search engine
1211:Constine, Josh (May 9, 2015).
674:Lyngbo, Trond (January 2013).
1:
888:Is This The Future Of Search?
1753:Wide area information server
1626:Search oriented architecture
1426:Trends in Cognitive Sciences
1333:Unnikrishnan, Srija (2013).
1042:. Venture Beat. 30 June 2014
1040:"Bing's twitter integration"
107:Research and implementations
1733:Search/Retrieve Web Service
1530:Collaborative search engine
1228:"Updating trends on mobile"
1086:Bailyn, Evan (2012-04-12).
973:. BBC News. 11 January 2012
890:, TechCrunch, July 16, 2008
841:10.1007/978-3-642-04441-0_5
804:10.1007/978-3-642-17155-0_3
1831:
1700:Website mirroring software
1616:Search engine optimization
1438:10.1016/j.tics.2014.10.004
1372:10.1016/j.cviu.2013.06.011
1241:Popper, Ben (April 2015).
1120:Burke, Amy (8 July 2013).
1064:. HubSpot. 15 January 2013
951:. HubSpot. 15 January 2013
507:Social information seeking
400:Despite the advantages of
69:that combines traditional
41:related search queries on
1685:Robots exclusion standard
148:. Former efforts include
83:algorithmic ranking model
37:such as news, videos and
18:Social discovery platform
1710:Web query classification
1690:Distributed web crawling
1257:"Google Semantic Search"
1201:, accessed 24 March 2023
996:"Google pushing Google+"
878:, Mashable, Aug 27. 2007
676:"What Is Social Search?"
1738:Search/Retrieve via URL
1611:Search engine marketing
714:10.1145/2766462.2767767
643:10.1145/2911451.2927018
482:Collaborative filtering
1631:Selection-based search
1310:10.1109/ICDCSW.2015.30
1166:"Social search engine"
492:Enterprise bookmarking
429:and resource handler.
152:. In 2008, a story on
35:user-generated content
1535:Cross-language search
1281:. EPrints. April 2009
1199:About Social Searcher
394:Peer to Peer networks
271:Social search engines
1304:. pp. 112–119.
586:. 30 September 2014.
427:zero knowledge proof
343:app feature called '
1621:Evaluation measures
1565:Video search engine
635:2016arXiv160504624H
497:Human search engine
446:social interactions
101:computer algorithms
1636:Document retrieval
776:2008-10-05 at the
760:10.1109/MC.2009.87
750:2012-10-03 at the
502:Relevance feedback
402:distributed search
397:broadband access.
390:distributed search
1787:
1786:
1661:Search aggregator
1570:Enterprise search
1525:Multimedia search
1520:Metasearch engine
1510:Web search engine
1344:978-3-642-36321-4
1319:978-1-4673-7303-6
1099:978-0-13-286140-3
850:978-3-642-04440-3
813:978-3-642-17154-3
467:Social Navigation
419:digital signature
222:In January 2013,
176:In October 2009,
16:(Redirected from
1822:
1656:Federated search
1489:
1482:
1475:
1466:
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1217:
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980:
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935:
933:
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926:on 18 March 2014
916:
910:
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818:
817:
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736:
735:
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690:
688:
687:
678:. Archived from
671:
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606:
605:
594:
588:
587:
576:
570:
569:
567:
555:
546:
545:
543:
542:
533:. Archived from
527:
472:Online community
462:Social Computing
450:wisdom-of-crowds
254:Social discovery
171:www.heystaks.com
92:online community
21:
1830:
1829:
1825:
1824:
1823:
1821:
1820:
1819:
1810:Social networks
1805:Social software
1790:
1789:
1788:
1783:
1757:
1720:
1714:
1675:Focused crawler
1606:Search by sound
1589:
1575:Semantic search
1545:Vertical search
1498:
1496:Internet search
1493:
1463:
1419:
1418:
1414:
1399:10.1145/2590974
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1186:
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1177:
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1148:
1144:
1135:Cubie, Gregor.
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778:Wayback Machine
769:
765:
752:Wayback Machine
743:
739:
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699:
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685:
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557:
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549:
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529:
528:
524:
520:
512:Social software
458:
423:blind signature
378:Semantic search
363:Tailored Trends
337:
273:
256:
209:Mark Zuckerberg
118:social networks
109:
28:
23:
22:
15:
12:
11:
5:
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1817:
1812:
1807:
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1792:
1791:
1785:
1784:
1782:
1781:
1776:
1774:Desktop search
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1393:(2): 1–23.
1139:. The Drum.
1124:. Mashable.
1024:23 December
702:"I See You"
434:user intent
309:Google Coop
261:mobile apps
259:enabled by
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1743:OpenSearch
1285:1 December
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1105:20 January
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518:References
415:encryption
345:Add a Link
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130:Jumper 2.0
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265:Facebook
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631:Bibcode
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