Design Patterns on Social Navigation


Published on

Published in: Design
  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Design Patterns on Social Navigation

  1. 1. HCDE 505 | Final paper | Ru-ping, Kuo Design Patterns on Social Navigation Ru-Ping, Kuo | ruping@uw.eduIntroduction The nature of hypertext is to make a website offering infinite ways of navigation to the visitors. True, thegoals among these visitors are diverse; however, no one wants to risk getting lost in an information space becausethey come here either to get information or accomplish tasks. In addition, there are plenty of other web sitesavailable; if visitors get lost at a web site or encounter a difficulty on navigation, they leave (Nielsen, 2003). Asthe result, web navigation design is continuously received significant attention over the past few decades. Manydesign principles, guidelines, and patterns are proposed in order to make a website capable or successfulsupporting these different information needs synchronously. While the ongoing growth of the World Wide Web(WWW), at the beginning of 2000s the term “Web 2.0” was introduced to characterize some emerging trends ininternet use such as “user-generated content (UGC)”, “social networking sites(SNS)”, “folksonomy” and“masups”. Although this change makes Tim Bemers-Lee’s vision of the web: “a collaborative medium, a placewhere we [could] all meet and read and write”1 becomes more accomplishable to all internet users, creating agood web navigation system also becomes a real problem to designers because of this change. In general, a good navigation design means that “people will be able to find, access, and use theinformation and services they need ‘efficiently’” (Kalbach, 2007). Today, more and more users come to a websiteare not only for “accessing” information but also for “creating” content and “sharing” them to others; these socialinteractions and two-way communications challenge the traditional navigation design strategies. As a websitemust become a “place” where can support and potentially foster social interaction, many researchers (e.g.Dieberger, 1997; Forsberg, Höök, and Svensson, 1998; Höök, Benyon, and Munro, 2003; Dourish, 2003;Svensson, Höök, and Coster, 2005) believe that social navigation plays an essential role to fulfill this need. Forexample, Svensson (2002) highlights two advantaged properties of social navigation: “dynamical” and“personalized”. Both attributes are reflecting a “bottom-up” fashion of navigation design, which stress that usersget to the right information by using “community wisdom” (Brusilovsky, 2008) rather than following thedesigner’s blueprint. According to Farzan (2009), the advantages of social navigation include: 1) help users filterout relevant information and decide where to go next; 2) add social texture by presenting how other users react to1 Tim Berners-Lee is the inventor of the World Wide Web. According to Wikipedia, this quotation is summarized from an interview (BBC News. 2005-08-09).Information is retrieved from, 1
  2. 2. HCDE 505 | Final paper | Ru-ping, Kuothe different content; 3) make information space more inviting by adding social affordance; 4) provide users morecontrol to reshape the information space. Hence, in recent years, social navigation has been applied to solve a diverse set of problems from websitenavigation to social software design (Wu and Bowles, 2010). However, a clear picture of social navigationsystems in practice on the web is still unavailable; as a result, web designers struggle to take advantage of socialnavigation. Meanwhile, many designers make good use of “design patterns library” when they encounter somesimilar problems because design patterns describe good solutions to recurring design problems in contexts(Pauwels, Hübscher, Bargas-Avila, and Opwis, 2010). With the development of the WWW, more and moresuccessful examples supporting that the social navigation as design thinking can supplement the former strategiesof navigation design. Therefore, I believe now will be the best time to look for answers of these questions: “Howsocial navigation systems are used on the web? What kind of websites particularly need to adopt social navigation?What kind of social navigation systems is used to solve what kind of problems? “ I also believe that the webdesign community will be beneficial by giving this primary study of design patterns on social navigation.Social Navigation The idea of social navigation is defined by Dourish and Chalmers in 1994; they consider social navigationas “navigation towards a cluster of people” or “navigation because other people have looked at something”(Höök, Benyon, and Munro, 2003). Couple years later, Dieberger (1997) widened the applicative scope of socialnavigation by introducing other web applications such as the earlier form of “social bookmarking” (sharingfavorite sites at personal webpages). The grounding of social navigation is based on that “information aboutothers and about others’ activities can be beneficial to an individual in the conduct of his or her activity. (Dourish,2003)” In another words, social navigation helps users by visualizing footprints of other users and adding socialaffordance about presence of others in an information space (Chalmers, Dieberger, Höök, and Rudström, 2004). Social navigation is a navigational activity and it is composed of at least five elements: a starting-point, adestination, the navigating agent, the route, and other agents with whom the navigating agent interacts. Theinteraction between the navigating agent and other agents is the key to make social navigation “social” (Forsberg,1998) and differ from the other types of navigation. Social navigation doesn’t have a narrow focus; Höök, Benyon,and Munro (2003) suggest that social navigation can be seen from several different perspectives and in severaldifferent domains. Many works and studies are covered five major areas: Human-computer interaction (HCI),Computer-Supported Cooperative Work (CSCW), Collaborative virtual environments (CVEs), Intelligent UserInterfaces (IUI), and Information Retrieval (IR) (Höök, Benyon, and Munro, 2003; Xu, Kreijns, and Hu, 2006).Farzan (2009) propsed the taxonomy of social navigation (see Figure 1) to illustrate the broad application of 2
  3. 3. HCDE 505 | Final paper | Ru-ping, Kuosocial navigation. The most popular way to classify social navigation is based on the types of communication :direct and indirect and it is proposed by Diberger Figure 1 Taxonomy of Social Navigation in Information Space(2000). The direct social navigation is oftenconsidered as synchronous and direct interactionbetween information provider and receiver(Farzan, 2009), but there are cases when it isbased on asynchronous communication (Svensson,2002). On the contrary, indirect social navigationfocuses on aggregated history informaiton (Farzan,2009). According to Svensson (2002), twocommon techniques for indirect social navigationare “collaborative filtering” and “history-enriched environments”.Social Navigation on the Web The advent of UGC and SNS makes today’s web space becomes more and more crowded withinformation and users. This type of modem websites demonstrate the “power of the collective” by allowingpeople to share experience and tacit knowledge, to make recommendations; it also enable people to get to knowother people and seek out affiliation, companionship and support from others (Girgensohn and Lee, 2002).Furthermore, this overwhelming power not only expands the production of Web content, but also ameliorates theways of information access because designers have taken the advantages of social navigation systems. Asdiscussion above, social navigation can help users get to the right information using “community wisdom” whichis distilled from tracked actions of those who interact with this information earlier. Although both direct andindirect social navigation systems can be applied in a web environment, the indirect and asynchronous approach ismore common in web applications. For example, one of the most well-known social navigation applications is thebook recommending mechanism at (Chang and Wang, 2011). More recently, the other types ofsocial navigation systems like social tagging and bookmarking system are also become familiar to internet usersbecause of some representative and successful websites such as and (Brusilovsky,2008). Since this study intends to review and evaluate how social navigation are used on the web by examiningpopular design patterns of social navigation closely and carefully, giving an overview of these applications isnecessary. Thus, several common and web-based social navigation systems are discussed as follows. 3
  4. 4. HCDE 505 | Final paper | Ru-ping, Kuo Recommendation System “Collaborative filtering” is the foundation stone of recommendation system. It also is one of earlier forms of social navigation systems. Collaborative filtering systems assume that people who agree on some things will likely agree on others, the more two people have in common, the more likely that one will like what the another one likes (Farkas, 2007). In this process, early users leave information clues that help later users make sense of the wealth of alternatives available to them (Konstan and Riedl, 2003). According to Konstan and Riedl (2012), today the mainstream of recommendation model is called “the personalized collaborative recommender”. This type of recommender is adopted by many popular websites: Amazon, Netflix,, and Facebook’s friend suggestions. Take as an example, the store radically changes based on customer interests. Moreover, rather than matching the user to similar customers, the “item-to-item” collaborative filtering matches each of the user’s purchased and rated items to similar items, then combines those similar items into a recommendation list (Linden, Smith, and York, 2003). However, it should be noted that current studies of recommender systems mostly focused on the techniques and computer algorithms to produce the right content of the recommendations, rather than the usability and user-related issues (Ozok, Fan and Norcio, 2010). Farkas (2007) points out that the systems based on the mathematical algorithms giving recommendation could be questionable, for example, just because one buys a book does not mean that he or she is actually happy with it; users might buy things for others; and the suggestions can also be misled when one account is used to choose items for more than one person. Comments (Customer Reviews) and Rating Systems Comments and ratings are the other well-known types of social navigation systems in present websites. Unlike the recommendation system collects data implicitly and without interrupt users, both rating and review systems are examples of explicit feedbacks which are provided by voluntary users. Accompanying the user rating and review system is widely adopt in many E-commerce (EC) sites, many researches has begun to investigate the influence of user-generated reviews on other consumers’ purchase decisions. Walther et al., (2012) summarized some important findings by carefully reviewing prior related studies, for instance, consumers apparently regard user-generated reviews as more trustworthy than traditional advertising information (Huang, Chou, and Lan, 2007); source characteristics associated with the author of a product review shape consumers’ perceptions of products (Forman, Ghose, and Wiesenfeld, 2006); and a variety of message features also affect responses (Dellarocas et al., 2005), such as valence, argument density, argument diversity, and the writer’s expertise claims. Moreover, compare to giving personal comments, the rating system is brief and it only requires minimal effort to users. A study shows that a rating without including a 4
  5. 5. HCDE 505 | Final paper | Ru-ping, Kuo comment may not be of great value for an end user, however, ratings provide the most reliable information for collaborative filtering and social navigation (Brusilovsky et al., 2010) Tagging Systems and Social Bookmarking The other notable mechanism of social navigation is the tag cloud. A tag cloud is composed of many keywords or terms (text links). The font-size of keywords is weighted by frequency (popularity). Kalbach (2007) claims that tag clouds are good for presenting content dynamically. Moreover, because tagging systems allow users to collectively classify information with their own words, they are also known as “folksonomy”. Although the social tagging has some drawbacks such as people can tag an item in many different ways (Farkas, 2007), it is applied at many different type of websites and content such as for bookmarks, Flickr for images, Technorati for blog posts, CiteULike for academic papers, or LibraryThing for books (Chang and Wang, 2011). In addition, the tag cloud is not the only form of tagging systems. Some other forms like “Navigating tags” or “Geotagging (a type of machine tag)2” are also used on the Web 2.0 sites frequently. According to Smith (2008), there are seven potential benefits for websites and organizations that adopt tagging systems: 1) facilitating collaboration; 2) obtaining descriptive metadata; 3) enhancing fundability; 4) increasing participation; 5) identifying web usage patterns; 6) augmenting existing classification efforts; 7) sparking innovation.Summary: Design Challenges of Social Navigation Although social navigation provides a promising opportunity to turn information space into a moresociable place, social navigation is not a concept that can be un-problematically translated into ready-made toolsand apply to an existing system or a web space directly (Konstan and Riedl, 2003). Social navigation requiresdesigners to think differently about the nature of people and their activities with communication technologies andenvironment (Höök, Benyon, and Munro, 2003). Svensson (2002) suggests several design questions that need tobe investigated by designers in order to successfully implement social navigation: “How actions should becommunicated between advice providers and advice seekers? Is there any privacy and trust issues concerningproviders? ”; “How will presence of others and their actions be mediated to advice seekers?”; “How socialnavigation fits into the overall system?” Since the concept of social navigation is new and widely applied in different type of computer andinformation environments, the universal evaluation criteria of social navigation still fall short of consensus.2 Unlike other tags, Geotags required a particular kind of structure metadata – geographic coordinates – to place resources on a map (Smith, 2008). According to Wikipedia,machine tag uses a special syntax to define extra semantic information about the tag, making it easier or more meaningful for interpretation by a computer program. 5
  6. 6. HCDE 505 | Final paper | Ru-ping, KuoHowever, many challenges and influential factors regarding to this matter are introduced by some researchers (e.g.Svensson, 2002; Svensson and Höök, 2003; Farzan, 2009), they are summarized as follows. 1. Social affordance (also known as the awareness of others and their actions): Users can learn what appropriate behaviors are if they can see the behavior of others. As the result, this awareness make users feel the web space is alive and more inviting. 2. Bootstrapping: Tthis issue also is named as “cold start” problem (Farzan, 2009). Social navigation systems often rely on the accumulated user behavior and feedback; as the result, early users will not have many social navigational aids. Hence, a very important challenge in developing social navigation systems is how to get the system started. 3. Drifts of interest: Over time, the interest of people and the importance of information are changed. Therefore, taking into consideration that different types of information have different expiration dates is important. Farzan (2009) proposes several solutions address this problem in her research paper, for instance, weighing more recent visits, and providing social navigation support based on the data from a specific period of time. 4. Snowball effects: Social navigation takes advantage of “collective wisdom”. However, a side effect occurs when more and more people walk down the “wrong” path because it will be indicated as a “preferred” path in a typical social navigation system. The snowball effect especially harms systems that rely mostly on implicit feedback from users. Farzan (2009) suggest that combining several types of implicit feedback can partially deal with this problem. 5. Privacy: This issue is raised because social navigation systems strongly rely on the visibility of people and their activities. Different people have different concerns about their privacy. Meanwhile, interpersonal trust also plays a significant role on social behavior of the system. Therefore, how the trust-privacy tradeoff can be optimized is the other needed consideration. Last, among these challengers, “social affordance” is the most common and essential factor thatinfluences social navigation design (Svensson, 2002). Many successful social navigation systems aimed at makingusers aware the social presence by providing “representations” of fellow participants and their activities (Cosley,Ludford, and Terveen, 2003). Erickson and Kellogg (2000 & 2003) developed a concept of “social translucent” toexplain why and how a CSCW system will be benefited by revealing and visualizing the presence and activity ofusers in digital environments. Moreover, there are three properties make a system socially translucent: 1)visibility: a system should allow users to see the presence and activity of others; 2) awareness: users should awarethat others can also see what they are doing when they can see others are doing; 3) accountability: sharedawareness leads to user accountability. It encourages users to follow social rules and norms since they know what 6
  7. 7. HCDE 505 | Final paper | Ru-ping, Kuoothers can notice their actions (Vassileva, 2009). Hence, in order to fulfill the need of social affordance, theseproperties of social translucent should also be took into account when design a social navigation system.Design Patterns: Design Solution in a Context Design is a problem solving process. Ideally, design solutions should originate from an explicitunderstanding of users, tasks and environments. However, in reality, designers may be forced to make decisionbased on their experience, knowledge and best-guess sometime. Under this kind of circumstance, design patternsas well as design guidelines are widely used to help designers communicating and evaluating design solutionsaccording to the relevant problem in its context. Thus, in recent years, the notion of design patterns has receivedconsiderable attention in web design. Van Duyne, Landay, and Hong (2007) claim that Design patterns solverecurring design problems, so designers can use pattern solutions to design their websites without reinventing thewheel. A typical design pattern describes the problem, the chosen solution, the rationale behind that solution, andrelated patterns that the designer should be aware of (Spool, 2003; Van Duyne, Landay, and Hong, 2007).Therefore, design patterns help a design team or an organization formalizing design knowledge and record bestpractices in the context. The other benefits of design patterns also includes: 1) reduce design time and effort onnew projects; 2) improve the quality of design osolutions; 3) Facilitate communication between designers andprogrammers; 4) Educate designers (Cooper, Reimann, and Cronin, 2007) because accordign to Alexander (1979)who is the concept of design patterns developer, design patterns were desinged to give non-professionals thepower to create good design as well (Pauwels, Hübscher, Bargas-Avila, and Opwis, 2010). My study plans to make good use of design patterns and adopt “pattern language” as the evaluateframework to examine how social navigation are used on the web today. On the other hand, integrating multiplerelated patterns into a pattern library brings higher value on design process (Pauwels, Hübscher, Bargas-Avila,and Opwis, 2010). Many web pattern libraries have been published either as books or online (e.g. Van Duyne,Landay, and Hong, 2007; Yahoo! Inc. 20063) but social navigation patterns are still lacking in. The finding of thisstudy might complete the absence of these patterns to the pre-exist pattern libraries in someway.3 Yahoo! Design Pattern Library 7
  8. 8. HCDE 505 | Final paper | Ru-ping, KuoMethods: Collecting and Evaluating Design Patterns of Social Navigation As discussed above, the essential value of design patterns Table 1 summary of study websitesis that patterns give proven and workable solutions. In anotherwords, design patterns are not derived from theory but identifiedas invariant aspects of solutions that emerge as best practices(Pauwels, Hübscher, Bargas-Avila, and Opwis, 2010). However,to identify these invariant design patterns from millions websitesfor evaluating with limited resource is the mission impossible tomy study. In order to ensure the quality of my study subjects(websites), I choose to generate a list of Top 50 sites in U.S fromAlexa.com4 and then screen out websites that do not meet thecriterion (subjects must use at least one type of social navigationsystems: recommendation, tagging, rating and review). As theresult, total 14 websites are selected (see Table 1 for summary).Among them, 31% is EC sites, 38% is UGC sites, 19% is SNS (n =14)sites, and 13% is others. It’s clear that these site genres confirmto prior researchers’ suggestions which were discussed in the earlier sections. In sum, certain types of websitessuch as Web 2.0 sites and EC sites are more depend on social navigation systems than other types of websites.Discussion: Social Navigation Patterns Site Genre Patterns Each “site genre” has similar content, goals, and users; therefore, Van Duyne, Landay, and Hong (2007) suggest the need to identifying the “site genre patterns” at first because this type of patterns is high-level and describing general properties and characteristics of certain type of sites.” Accordingly, I found that different type of websites adopts design patterns of social navigation systems differently. The difference between EC sites and UGC sites is distinct; meanwhile, SNS sites genre patterns share some common traits with UGC sits. 1. EC sites (& provides traffic data, global rankings and other information on thousands of websites, and claims that 6 million people visit its website monthly. 8
  9. 9. HCDE 505 | Final paper | Ru-ping, Kuo EC sites promise to make online shopping experience is easier and more enjoyable (Van Duyne, Landay, and Hong, 2007). Moreover, the business goals of an EC site are encouraging visitors to stay longer and browse more items. As the result, the recommendation systems become a magical solution fulfill the needs. The recommender plays as a salesclerk or a shopping consultant in a virtual store. More importantly, this sales assistant has amazing memory. She is not only able to remember the specific location of every item in the store but also know everything about customers and their shopping preference and history. She is an expert on almost everything, too. She could suggest things that customers might like or even not aware they might need from many different aspects. Hence, EC sites provide various recommendations at the same time, for instance, “customers who viewed/bought this also viewed/bought…”; “frequently bought together”; “what other items do customers buy after viewing this item”. Moreover, compare to UGC and SNS sites, EC sites’ rating systems are more polished and join with review systems together since trustworthiness plays an important influence on online purchase decisions. In some cases, users even can give their rating and comments to sellers as well as products. There is no any EC site adopts tagging system in my study. 2. UGC sites UGC sites use social navigation systems differently because they face different challenges. First, almost every UGC site takes advantage of tagging systems because the tagging enhances findability and makes the information structure more flexible, extensible, and aggregatable (Smith, 2008). However, in order to reduce the bootstrapping effect, the “multiple ways to navigate pattern5” is adopted, too. For example, uses Geotagging system adding location tag upon users’ photo and allows users exploring photos by place, date, and even camera brand (these are all “machine tags’). Moreover, rating system is more easy to use. Besides the form of rating starts is replaced by one “favorite” button (or “like” and “dislike” buttons), it also works independently (rating and comment are two individual systems in general). Last, compare to EC sites, UGC sites’ recommendation systems are usually implicit, simple (some are shown as text links) and single. 3. SNS sites Unlike the other two types of websites’ social navigation systems are more focus on things (products, photos, articles etc.), SNS sites concentrate on human and how to promote social awareness through social navigation systems. Many forms of social navigation systems are altered in order to fulfill the needs, for instance rating, re-post/re-pin (adapt from the comment systems), and follow. In short, the design patterns of SNS sites’ rating and review systems are close to UGC sites than EC sites. Moreover,5 See Van Duyne, Landay, and Hong’s (2007) book for detail. pp. 216-220 9
  10. 10. HCDE 505 | Final paper | Ru-ping, Kuo the role and patterns of recommendation system in SNS sites are diverse. For example, the recommendation pattern in is similar to other genres but push content to users’ personalized home page according to a group of interests. Moreover, unlike UGC sites and EC sites, the recommender is designed as a component of web pages, put recommendations design patterns on the whole start page in order to create “dynamical” and “personalized” user experience to the members. Recommendation Patterns The keystone of recommendation pattern is using “collaborative filtering” approaches to build an algorithmic model based on users’ past behavior. However, from a user point of view, no matter how the mathematical algorithms giving recommendation in behind, the whole point is that weather these recommendatory items are related to his or her interest? Therefore, the goal of this pattern is to predict and satisfy every user’s unique needs based on collective wisdom. [Problems] The recommendation pattern is usually used to solve these problems or fulfill these needs: 1) When visitors have no clear or specific ideas about what they need, or what other things they can find from this website; 2) To encourage visitors stay longer, see more content (items), or buy more items; 3) Provide alternative ways to navigate the website; 4) Enhance visibility and fundability of content (and/or users); 5) Provide alternative ways to compare items; 6) Save visitors’ time and effort on browsing or navigating; 7) Provide personalized service to visitors. 8) Want to make good use of community wisdom. 9) When a website has a huge collection of content and the content is continuously growing. In addition, a website can constantly refine and improve the information structure and user experience design by aggregating and analyzing these use data. [Solutions] Use multiple sources to generate the recommendatory list (e.g. Amazon’s item-to-item” collaborative filtering model) instead of using single and purely inferred data to make recommendations. The form and placement of recommendation patterns can be various, but each recommendatory item should include its photo and some important information (depends on the purpose of the recommendation). If possible, use clear label address how is the recommendation generated from (e.g. personal browsing history, other users’ activities, similar topics, popularity etc.). SNS or UGC sites should consider including provider’s (creator’s) handle name for enhancing social awareness. Moreover, provides other useful information such as date, rating, and popularity (e.g. total views) for helping visitors filter out most attractive item. By doing so, “the snowball effects” might be reduced, too. Finally, if the placement of advertising is apposition to recommendation systems, make sure users are able to recognize advertisements different from recommendations. Users Comments/Reviews and Rating Patterns Researches show that people read “user reviews” in order to weigh their decision when shopping online (e.g. Huang, Chou, & Lan, 2007; Mudambi and Schuff, 2010). On the other hand, many SNS and UGC sites provide comments system in order to support social interaction and encourage users participated in community. These patterns might play different roles on different types of websites but their goal is alike. 10
  11. 11. HCDE 505 | Final paper | Ru-ping, Kuo These patterns are used to support two-way communication. In the end, the website become more alive and appeal to visitors by providing social affordance. [Problems] The user comments/reviews and rating patterns are usually used to solve these problems or fulfill these needs: 1) To encourage participations and social interaction; 2) To encourage visitors stay longer, see more content (items), or buy more items; 3) Create an environment where cultivate rich and various voices (opinions); 4) Want to make good use of community wisdom; 5) Provide alternative ways to prioritize content (items); 6) Enhance credibility; 7) Provide convenient ways for users to share the opinions; 8) Help users make better decision; 9) Enhance social awareness. [Solutions] Provide a ship to multiple addresses action button and make they are obvious and easy to use. For example, actively invites and reminds customers provide feedback from many ways. Although people usually enjoy sharing their ideas, they might also unwilling to share if it required too much efforts. Therefore, the feedback systems should be easy to learn, easy to use, and give clear instruction. Websites also should provide different tools (required different levels of effort) for users to share their opinions. Take as an example, users can write a customer review and give the rating (require login), press “like” button (no login required), or comment other users’ comment. As soon as users provide their opinion, the system should give clear feedbacks to users. The systems also should provide ways for users tracking, monitoring, or even revoking their sharing (both comments and ratings). Create an enjoyable and interesting sharing experience for users in order to encourage their sharing behavior. More importantly, try to make these patterns as social translucent as possible if the design does not against users’ privacy concerns. Tagging Patterns Although the usefulness of some tagging patterns such as tag clouds is still under debated, the concept of “folksonomy” makes tagging system stand out from the other types of navigation in website design. Smith (2008) describes tagging system as “people-powered metadata for the social web”. The unique advantage of tagging patterns is it allows users to organize and labeling information with their own way although tags also can be created by machine automatically (by defining semantic information). [Problems] The tagging patterns are usually used to solve these problems or fulfill these needs: 1) When visitors have no clear or specific ideas about what they need, or what other things they can find from this website; 2) To encourage visitors stay longer, see more content; 3) Enhance social awareness; 4) Provide alternative ways for users to organize and navigate content (bottom-up); 5) To obtain and aggregate metadata from users point of views; 6) Made good use of community wisdom; 7) Provide alternative ways to prioritize content; 8) Help users to find and interact others users who have similar interests; 9) When a website has a huge collection of content and the content is continuously growing; 10) Enhance visibility and fundability of content (and/or users); 11) When content are generated by users; 12) To create a semantic web. [Solutions] Tag clouds are a powerful solution to present all tags associate with a subject or with the whole website. Usually a tag cloud presents tags alphabetically and then enlarges the tags proportionally based on popularity. It provides more information cues than the general hierarchical structure of information. It also is a good way to show users a visual representation about a virtual community’s most general activities. However, there are many forms of tagging systems (tag clouds, navigation tags, Geotagging, etc.) and it is important to provide multiple navigating ways to users in order to reduce some negative effects of social navigation such as “drifts of interest” or “bootstrapping”. 11
  12. 12. HCDE 505 | Final paper | Ru-ping, Kuo presenting many great and successful tagging patterns that other UGC and SNS sites can imitate. In addition, Smith (2008) introduce several ways to motive user tagging, for instance, help users use tags expressing themselves or managing personal information and social information.Conclusion Although social navigation has been proposed as a means to make information space becomes moresocial and easier to navigate (e.g. Dieberger, 1997; Höök, Benyon, and Munro, 2003; Dourish, 2003), a lack ofcommon and interpretive frameworks makes it difficult to unpack and adopt to design process effectively. But atthe same time, there are plentiful well-known and successful examples on the web demonstrating the capability ofsocial navigation systems. Thus, this study first carefully investigates and discusses related concepts of socialnavigation from the literatures review, and then identified three popular social navigation systems:recommendation, ratting and reviews, and tagging which are widely applied on the web. Next, I take “designpatterns” as the study approach; carefully examined many popular websites in order to reveal the current status ofsocial navigation in practice. The results of my empirical study confirm scholars’ expectation of social navigation. It’s clear that certainwebsites like SNS, UGC and EC sites rely on social navigation systems than other types of websites. Thistendency provides evidences supporting that social navigation can supplement the emerging need of socialinteraction on the social software. It also suggests that the social navigation provides the solutions for designer tohandle the rapid growing and unpredictable content which are generated by users. Unlike traditional navigationtend to focus on “efficiency of information retrieval”, social navigation is flexible to use on different informationnavigate needs. For instance, recommendation systems help users either explore more items or find the item theyneed quickly because this system can predate users’ information needs. Furthermore, my finding also discoveresthat the unique character of social navigation allows designers use it in other application such as “re-pin” and“follow”. Both “re-pin” and “follow” are familiar function to most SNS users although these two functions areusually not considers as kind of social navigation patterns in general. Finally, there are several limitations of my study should be mentioned. First, my study only examined 14websites because of the limitation of resource. I expect that more different patterns of social navigation can bediscovered if I reviewed more websites. Moreover, in general, a design pattern should suggest other relativepatterns in order to make it more useful. However this part does not include because my study intent to examinebest practice of social navigation systems on the web and depict them with pattern language framework ratherthan develop a complete set of design patterns of social navigation. 12
  13. 13. HCDE 505 | Final paper | Ru-ping, KuoReferencesA. Ant Ozok, Quyin Fan, and Anthony F. Norcio. (2010). Design Guidelines for Effective Recommender System Interfaces Based on a Usability Criteria Conceptual Model: Results from a College Student Population. Behaviour & Information Technology, 57–83.Alan Cooper, Robert Reimann, and David Cronin . (2007). About Face 3: The Essentials of Interaction Design. Wiley.Andreas Dieberger. (1997). Supporting social navigation on the World Wide Web. Int. J. Human Computer Studies, 805-825.Andreas Girgensohn and Alison Lee. (2002). Making Web Sites Be Places for Social Interaction. CSCW 02. New Orleans, Louisiana, USA.Dan Cosley, Pamela Ludford, and Loren Terveen. (2003). Studying the Effect of Similarity in Online Task-Focused Interactions. Group 03. Sanibel Island, Florida, USA.Douglas K. Van Duyne, James A. Landay, and Jason I. Hong. (2007). The Design of Sites: Patterns for Creating Winning Web sites. Pearson Education Inc.Greg Linden, Brent Smith, and Jeremy York. (2003). Recommendations: Item-to-item Collaborative Filtering. Internet Computing, IEEE, 76-80.Hsia-Ching Chang, and Chen-Ya Wang. (2011). No Cue, No Clue? Understanding Information Interaction in Social Bookmarking Services. 2011 Eighth International Conference on Information Technology: New Generations. Las Vegas, USA.Jakob Nielsen. (2003). Usability 101: Introduction to Usability. Retrieved from Kalbach. (2007). Designing Web Navigation. O’Reilly Media, Inc.Jared M. Spool. (2003). Design Patterns: An Evolutionary Step to Managing Complex Sites. Retrieved 12 10, 2012, from A. Konstan and John Riedl. (2003). Collaborative Filtering: Supporting Social Navigation in Large, Crowded Infospaces. In Munro, A., Höök K. & Benyon D. (Eds), Social Navigation of Information Space, pp. 43-82.Joseph A. Konstan and John Riedl. (2012). Recommended for You. Spectrum, IEEE, 54 - 61.Joseph B. Walther, Yuhua (Jake) Liang, Tina Ganster, Donghee Yvette Wohn, and Josh Emington . (2012). Online Reviews, Helpfulness Ratings, and Consumer Attitudes: An Extension of Congruity Theory to Multiple Sources in Web 2.0. Journal of Computer-Mediated Communication, 97-112.Julita Vassileva (2009). Social Interaction History: A Framework for Supporting Exploration of Social Information Spaces. International Conference on Computational Science and Engineering. Vancouver, Canada.Kristina Höök, David Benyon, and Alan J. Munro. (2003). Footprints in the Snow. In Munro, A., Höök K. & Benyon D. (Eds), Social Navigation of Information Space. pp. 1-11.Martin Svensson. (2002). Defining, Designing and Evaluating Social Navigation. ph.D. thesis, Stockholm University. 13
  14. 14. HCDE 505 | Final paper | Ru-ping, KuoMartin Svensson and Kristina Höök. (2003). Social Navigation of Food Recipes: Designing Kalas. In Munro, A., Höök K. & Benyon D. (Eds), Social Navigation of Information Space. pp. 201-222.Martin Svensson, Kristina Höök, and Rickard Coster. (2005). Designing and Evaluating Kalas: A Social Navigation System for Food Recip. ACM Transactions on Computer-Human Interaction, 374–400.Matthew Chalmers, Andreas Dieberger, Kristina Höök, and Åsa Rudström. (2004). Social Navigation and Seamful Design. Cognitive Studies, 1-11.Mattias Forsberg, Kristina Höök, and Martin Svensson. (1998). Design Principles for Social Navigation. 4th ERCIM Workshop on User Interfaces for All, Special Theme "Towards an Accessible Web". Stockholm, Sweden.Meredith G. Farkas. (2007). Social Software in Libraries: Building Collaboration, Communication, and Community Online. Information Today, Inc.Min Wu and C. Travis Bowles. (2010). Principles for Applying Social Navigatin to Collaborative Systems. CHIMIT’10. San Jose, USA.Paul Dourish. (2003). Where the Footprints Lead: Tracking down Other Roles for Social Nvigation. In Munro, A., Höök K. & Benyon D. (Eds), Social Navigation of Information Space, pp. 15-34.Peter Brusilovsky. (2008). Social Information Access: The Other Side of the Social Web. SOFSEM 2008. Novy Smokovec, High Tatras, Slovakia.Peter Brusilovsky, Lillian Cassel, Lois Delcambre, Edward Fox, Richard Furuta, Daniel D. Garcia, Frank M. Shipman III, Paul Bogen, and Michael Yudelson. (2010). Enhancing Digital Libraries with Social Navigation: The Case of Ensemble. ECDL 2010. Glasgow, UK.Rosta Farzan. (2009). Study of Social Navigation Support under Different Situational and Personal Factors. ph.D. thesis, University of Pittsburgh.Stefan L. Pauwels, Christian Hübscher, Javier A. Bargas-Avila, Klaus Opwis. (2010). Building an Interaction Design Pattern Language: A Case Study. Computers in Human Behavior, 452-463.Susan M. Mudambi and David Schuff. (2010). What Makes a Helpful Online Review? A Study of Customer Reviews on MIS Quarterly, 185-200.Thomas Erickson and Wendy A. Kellogg. (2000). Social Translucence: an Approach to Designing Systems that Support Social Processes. ACM Transactions on Computer-Human Interaction, 59–83.Thomas Erickson and Wendy A. Kellogg. (2003). Social Translucence: Using Minimalist Visualisations of Social Activity to Support Collective Interaction. In Munro, A., Höök K. & Benyon D. (Eds), Social Navigation of Information Space, pp. 17-42.Wen Xu, Karel Kreijns2, and Jun Hu. (2006). Designing Social Navigation for a Virtual Community of Practice. Edutainment 2006. Hangzhou, China. 14