Social Search Interfaces in Information Retrieval Jennifer Kott College of Information Science and Technology, Drexel University Jmk376@drexel.eduABSTRACT Google and Microsoft have come out with two good collaborationThis paper examines social web search, collaborative interfaces interfaces which support social search. User studies from both oftools and their role in seeking information. The literature these interfaces are reviewed in this paper. Study one looks atreferenced in this paper, is a combination of several studies on FeedMe, a plug in for Google. FeedMe is a behind the scenes wayuser preference, habits and how users share information using of sharing content with friends by sharing links. . FeedMecollaborative interfaces. prompts users to share web links with friends and asks them their opinion on what was shared. Another study tested theParticipates of the collaboration tool studies were chosen at SearchTogether a browser plug-in from Microsoft. .random and paid for their responses. Feedback was given based SearchTogether is a real-time collaboration tool giving users theon user experience and testing of software features. Collaboration opportunity to view fellow user’s searches and socialize withsoftware evaluated included: FeedMe, SearchTogether and them during the searching process.Coagmento. Each study lasted a period of about two weeks. Theuser habit models discussed includes: the Random Walk Model, The goal of each user study was to measure the productsResource Recommendation Model, Tagging Model and Link effectiveness as a collaboration tool. Side benefits of each studySharing. were user suggestions on product enhancements which would make collaboration easier. The first step to making improvementsTo create better collaboration tools you need to evaluate the on collaborative interfaces is to fully understand how social filesexisting ones and identify where improvements can be made. In sharing works. We do that by first examining user habits,these studies, the users identified a few areas where tools could preferences and users need to share information.help with improving content sharing. For example, privacyconcerns were noted in the FeedMe study. Users made a 2. LITERATURE REVIEWsuggestion to help with the privacy issue. They requested that a Literature shows, user preferences play a key role in determiningpublic knowledge trigger be added to the software. What is how successful the social sharing will be. User preferences in theunclear is what will happen if the public knowledge trigger fails. literature showed users shied away from the advanced searchWould the creators of the FeedMe tool be held liable? features in favor of smaller searches. It’s not clear why, but twoCreators of collaboration tools need to take things slow. theories point to anything from a lazy user to lack of knowledgeAdditional studies need to be done comparing the benefits versus when searching.  The user tends to use multiple word queries tolegal implications of changing some of the collaboration tools. search for information or relays on others to find information forUsers may play a very important role in determining the them. On more advance searches users typical involve librarians.collaboration tools of the future. Identifying a user as lazy maybe a bit harsh, a more reasonableCategories and Subject Descriptors explanation may point to the preparation of the user prior toH5.2 . Information interfaces and presentation (e.g. HCI) engaging in the search. Users who take the time to plan, organize and set goals prior to seeking information tend to have moreGeneral Terms successful outcomes.  The figure below illustrates a three stepDesign, Human Factors, Verification. process a user goes through when seeking information. We break each step by; 1) purpose, 2) gathering of requirements and 3)Keywords formulate representation. 68.7 % were self-motivated searchesSocial link sharing, blogs, RSS, social search, navigational search, amd 31.3% were motivated by some type of external source. query, tagging, taxonomy, informational, user-centered, socialcollaboration, personalization, data.1. INTRODUCTIONThe search for information has become more of a collaborativeeffort. Methods of sharing information have evolved over the pastfew years with WEB 2.0. Web users can not only submit contentbut enhance it through personalization. A magnitude ofinformation is out on the internet for users to sift through, makesense of, to find what is relevant. Studies into online behaviorshow users will seek help from others when having difficulty Figure 1. Shows prepartion prior to seeking information. (Evans, 2009)locating information online. A recommendation by another usercan aid in that search. Recently developed interfaces help tosupport different types of searches.
2.1 User Preferences by speeding up retrieval relevant content because it shorten theUser habits and preferences are only one aspect of understanding number of clicks needed to locate the content.the user. Equally important is an understanding of what the user is This diagram shows how the random walk model works. Side (a)searching for. The three types of searches discussed in the illustrates the synonym part of the model and side (b) illustratesliterature include navigational, transactional, and informational. the homographs using user preferences.Literature suggests social search works best the informational typesearch. In an information search, users are on a journey to seek outrelevant information. They do not follow a specific path to findinformation and may not be familiar with the topic. This type ofbehavior is known as forging. In forging for information usersstart in one direction and may be led into another direction by asimple click. In social search, users are influenced by their peersoften leading them different directions. Interfaces like CiteULikeand Del.icio.us help users gather the forged information. Thesetwo systems are social tagging systems. Social tagging links theuser to a resource. Figure 2: Random walk model (Clements, 2009)It’s important to note, a tagged resource does not meanautomatically equal a good resource. Users need to keep in mind,a tag is a recommendation, and other factors may play into the 3.2 Resource-recommendation Modelreason why a resource was tagged. These factors may includeeducation and interests of tagger. When seeking information the The Resource-recommendation model examined the socialresults need to be deemed relevant and creditable in order to be tagging behaviors and time and tagging behaviors of users. Theuseful. study used tag and time behaviors to come up with ratings using a dataset from CiteULike. The recommended resource model used2.2 User Opinions tag-weight rating, time-weight rating and a tag time rating.Research varies on the usefulness of tagged content but tagged Overlapping ratings combined to form a user similaritycontent used in conjunction with user opinions carries more calculation. The output of the model is the recommendedweight. Rating systems built into interfaces allow users to rate the resource. The diagram below illustrates the framework of thequality of the content. Content is put in to specific categories Resource-recommendation model.based on each rating. Placing content into specific categories,based on a rating given by a user, is still seen as subjective Content chosen based on a rating system is flawed, because therating is based on opinion rather that fact.3. Tagging ModelsA side benefit of social tagging and rating is building content.LibraryThing keep track of books they have read, tag them andrate them. Users can use the benefits of tag and rating to findrecommend reading on various subjects of interest. The study onLibraryThing showed the parallel between number of tags andnumber of web searches.  In LibraryThing, users tag contentfor a variety of reasons. A tag can be used to describe content, alocation or a status. Tags are good for putting books in to specificcategories. Tagging is another way to help users find content.3.1 Random Walk Model Figure 3. Framework: Resource recommendation Model (Zheng,Vocabulary remains a hurdle in many tagging systems. Variations 2010)in words, use of synonyms and homographs have a directly affecton search results. Similar problems occur in plural forms of thewords. To overcome this hurdle, a studying using a method calledclustering. Clustering puts tags into groups, groups were 3.3. Link Sharingdetermined by how closely they relate to each other. Link sharing is another form of sharing content. A survey The Random Walk Model looked at the outcomes of clustering conducted by 40 web users asked four basic questions on linkwhen synonyms were used. These clusters helped improve sharing: 1) What tools do you use to share content 2) How do yououtcomes. Shorter queries of four or less terms showed the best go about finding and reviewing new web content? 3) Which is theresults. strongest motivator when you share links? 4) Which is the biggest concern you have when you share links?To overcome the homograph hurdle evaluators used the same Findings of the survey show email as the number one method ofrandom walk model to pair up the query tag and the target user sharing content. Favorite ways of discovering new content werepreference. The matching of user preference to query tag worked, visiting favorite websites a few times a week and receiving URLs via email from unknown recipients. What motivates a user to
share a link? Answer given most often, they thought the topic features in SearchTogether include thumbs up/down, peek andmight interest the other person. A respondent were uncertain on follow browsing and on-line chatting via a add/comment box. the links relevance to the other user but shared them anyway. Amain worry among users was the possibility of too much email The user study published by Morris & Horvitz, 2007b andbeing forwarded to one person. evaluated by Wilson  highlighted four areas where users wished to have better control over collaboration. In peeking andUser sharing habits showed a tendency to share link more following, users wanted to know who is peeking and who isprevalent between friends over someone they did not know. The following them. Rights to see the same URL another user issurvey theorized this was because friends know the interests of currently viewing and being able to push pages to other users withtheir friends the best. For example, if your friend liked to cook ease. Along with the flexibility, to edit and annotate any searchand you came across a recipe, you would be more likely to share summary pages.the recipe with your friend over a stranger whose taste you are notfamiliar with. 4.3 Coagmento Coagmento a plug-in from Firefox helps remote workers4. SOCIAL SEARCH communicate, search, share and organize information over theSocial search defined in the literature as social interactions with web.  There are several good collaboration tools inside of theothers  Interactions can be explicit or implicit, co-located or Cogmento plugin. Information collection tools help users createremote, synchronous or asynchronous. (Evans, 2009) To get users annotations and save and remove webpages. To help withengaged socially the collaboration software must be easy to use. collaboration a side panel is equipped with a chat window and aThe fact is, a user who needs to jump through hoops to share history of search engine queries, saved pages and snippets forinformation won’t bother do it! In theory, a good collaboration users to exchange thoughts and ideas. tool gives user’s a variety of ways to communicate, share, searchand organize information. This study focused on awareness in CIS. It used 84 participates from the University of North Carolina at Chapel Hill and4.1 FeedMe measured three conditions; Contextual awareness, work spaceTo test this theory, a study conducted over a two week period of awareness and examined the workspace area provided for grouptime followed 60 users of FeedMe. FeedMe prompts users to collaboration. Personal peripheral awareness measured how wellshare web links with their friends and asks them to give feedback the interface supported user’s personal history including, savedon content shared. The purpose of the study is to gain a better documents, snippets and queries. Group peripheral awarenessunderstanding of the user. What features do they like? What looked at the same thing as personal peripheral awareness butfeatures could be improved in the software? from a group level perspective.A few key things were learned from the FeedMe study. Features A key outcome of the Coagmento awareness study showed theusers scored most favorable were the one-click thanks feature and design of the Coagmento interface supported group awareness forthe later instead of now feature. The one-click thanks feature is an synchronous collaboration the best.  The product received lowautomated response to thank the person sending you the link. The marks in the area of personal awareness. Group users had nolater instead feature is a view into the receipts email box. If the problems keeping up on the status of projects. They had fullsender thinks the recipient already has too many links waiting to visibility into what each member of the project was working on atbe viewed, they can schedule the link to show up later. The later all times and were able to collaborate with them through multipleinstead feature scored favorable among users because it allowed phases of the project.users to share information in a polite way as to not overwhelm the Reported as unfavorable under group awareness was the lack ofrecipient.  real-time collaboration. Users suggested some type of sharedUser privacy concerns were one alarming finding of the study. notepad workspace be added to help with the real-timeUsers feed recommended topics into the system based system collaboration issues.  Coagmento was designed forsuggestions of each user’s interest. Sharing information collaboration in synchronous or asynchronous mode. To supportconcerning a disease, could potentially tip off other users to a synchronous-remote collaboration some major changes would behealth issue. Suggestions on how to fix the privacy issue, called need made to Coagmento. Another suggestion s was some type offor a trigger called public knowledge to be added to the interface. alert system when new information added from a fellow groupThe public knowledge control would be set by the user.  Only member. An alert would be helpful in those situations when a userthe public knowledge topics deemed by each user would show up needed to pick up some critical information about a task or aas their interests. Users would decide when a topic was safe to change in a project.discuss and when. This approach sounds reasonable but it’sunclear if users would really take the time to setup public 5. Research Gapsknowledge triggers. Additional studies would need to be done in A look at the data from all three user group studies show gaps inthis area. some of the research. Privacy and users rights to privacy are missing. We do not know if any of the interfaces tested do a good4.2 SearchTogether job at protecting the user’s right to privacy. Are some interfacesSearchTogether from Microsoft is effective for those who like to better than others when it comes to protecting the user’s privacyscan for information or learn from information. It supports large or is the burden of protecting private information solely on thegroup collaboration by using group queries histories and split shoulders of the user? This question remains unanswered. Onesearching. SearchTogether is not a structured search tool. Instead user pointed to privacy concerns in the FeedMe study byit’s for the user who is not sure what they are looking for. They suggesting the need for a public knowledge trigger. A publiccould just be browsing for ideas or information. Collaborative knowledge trigger would aid in protecting privacy concerns of the information sharer but only if the user the trigger. Automatic
privacy protection needs to be built in to all of the products for it the user to share information, it appears more work is needed into be useful. the area of protecting the user’s privacy. Until interfaces can protect the user’s privacy the benefits of social search may onlySocial searching does not mean users have a right to know all of be shared friends.your private business. A check box in the interface can helpfiltering what information you wish to share and when. Results 7. REFERENCESfrom the Coagnento study had users request more real-time  Bernstein, M.S., Marcus, A. Karger, D. R. and Miller, R.C.collaboration tools when working with remote users. Real-time (20100. Enhancing directed content sharing on the web.collaboration could be seen as a major benefit when working on NewYork, N.Y : In Proceedings of the SIGCHI Conferenceprojects in a group. Unclear in the study is who made this on Human Factors in Computing Systems (CHI 10). ACM,recommendation? Was it a user or did management request such a pp. 971-980. DOI=10.1145/1753326.1753470tool as a way to keep tabs on off-site workers? A may give up http://doi.acm.org.ezproxy2.library.drexel.edu/10.1145/1753some of their rights to privacy in a real-time collaboration 326.1753470interface.Similar privacy concerns are noted using the peek and follow  Clements, M., de Vries, A.P., and Reindeers, M.J. T.( 2009).features in SearchTogether. In SearchTogether users have rights The influence of personalization on tag query length in socialto know who is peeking and who is following them does the user media search. Information Processing & Management,have rights to stop a user from peeking and following? If so are Volume 46, Issue 4, July 2010, pp. 403-412Tavel, P. 2007.the tools adequate to protect the user’s privacy? Modeling and Simulation Design. AK Peters Ltd., Natick,All three studies did a good job of asking users their which tools MA.were useful to them and which ones could be improved. The  Evan, B.M. and Ed. H.Chi. 2009. An elaborated model ofsocial sharing of information requires a collaborative interface social search. Information Processing & Management,which helps protect the user and their privacy. Needs will only Volume 46, Issue 6, November 2010, pp. 656-678.continue to grow as more gadgets are invented to support socialsearch participation.  McDonnell, M. and Shiri, A.2011. Social search: A taxonomy of, and a user-center approach to, social web6. CONCLUSION search. Program: electronic library and information systems,The information seeking behaviors of the users show content Vol. 45, Iss.: 1 pp. 6-28. Emerald Group Pub. Ltd. 0033-sharing on the web is here to stay. This paper took a look at some 0337 DOI 10.1108/00330331111107376of the collaborative interfaces used in social search on the web  Wilson, M. L. and Schraefel, M.C.(2010) Evaluatingand asked users to rate their effectiveness. Feedback from the user collaborative information-seeking interfaces with a search-studies like the ones reviewed in this paper can help developers oriented inspection method and re-framed informationbuild better tools to share information. seeking theory. Information Processing & Management, Volume 46, Issue 6, pp. 718-732 The other pieces of the social search puzzle include an http://www.sciencedirect.com/science/article/pii/S030645730understanding of user habits. What prompts the user to share 9001125information? Is it the tool, the subject matter or is it therelationship with the other user? The links sharing study pointed  Shah, C. and Marchionini, G. (2010), Awareness into user relationship as the catalyst to sharing a link. Sharing a link collaborative information seeking. J. Am. Soc. Inf. Sci., 61:with a friend was far more prevalent than sharing a link with a 1970–1986. doi: 10.1002/asi.21379stranger. This finding was not surprising, because users are morecomfortable around friends and they know the interests of their  Nan Zheng, Qiudan Li, 2010. A recommender system basedfriends the best. So why not share information with them? on tag and time information for social tagging systems,If we want users to step outside of their comfort zone and share Expert Systems with Applications, Volume 38, Issue 4, Aprilinformation with strangers we need to build interfaces which 2011, pp. 4575-4587, ISSN 0957-4174,support, ease of use, anticipate what a user is searching for and a 10.1016/j.eswa.2010.09.131.way to protect the user from invasion of privacy. http://www.sciencedirect.com/science/article/pii/S095741741 0010882 This paper identifies a few gaps in the studies with regards touser’s privacy. Developers have worked hard at adding featuressupportive of collaboration. All with the aim to make it easier for