Information Architecture & Design Week 6 Schedule Class Work First! Research Topic Presentations Browsing and Searching for IA Other Readings

Card(Term) Sorting for Site Labels Why Card Sorting So Early? Multiple Applications of this Technique, unfortunately known (only) as Card Sorting Rosenfeld: Two Kinds of Labels Subject Matter Expert Labels Lay Person – Novice Labels Focus on Needs & Problems with Labels Categories of Labels help with Design Scope

Lable Sorting – Speed Sorting How Much Time Will Users Spend Deciphering Your Site? A Series of Quick Label Evaluations Terms Phrases We’ll Do Traditional Card Sorting Later in the Semester

Sorting Step 1 Look at all the terms & phrases Each of you: write a 1 sentence description of what the site these terms and phrases must be about. 2 Minutes!

Sorting Step 2 Read over the terms and phrases and circle the ones you immediately & certainly understand. 2 Minutes! Read over the terms and phrases and lightly cross out terms and phrases you don’t understand.

Sorting Step 3 Work together: suggest terms and phrases for the circled items. Provide up to 3 alternatives. Focus. 3 Minutes! Work together: suggest terms and phrases you crossed out. Provide up to 3 alternatives. Create.

ROTATE Label List! Each Group: Work with Another List All Three Steps Again. Turn Over Work to Original Project Group After Class: Tighten Up Vocabulary Consistency of Use (Nouns – Verbs) Fix Cases, Spelling, Parallel Word Counts What’s Missing?

Browsing and Searching Information Seeking Using Models Understanding Navigation Designing Navigation Choo, C. W., Detlor, B., & Turnbull, D. (2000). Information Seeking on the Web: An Integrated Model of Browsing and Searching. First Monday, 5(2). Tauscher, L. M., & Greenberg, S. (1997). Revisitation patterns in World Wide Web navigation. Paper presented at the ACM SIGCHI '97, Atlanta, GA. Bates, M. After the dot-bomb: Getting Information Retrieval Right This Time. First Monday. 2002. Kobayashi, M., & Takeda, K. (2000). Information Retrieval on the Web. ACM Computing Surveys, 32(2). Maglio, P., & Barrett, R. (1996). How to Build Modeling Agents to Support Web Searchers. Paper presented at the Sixth International Conference on User Modeling, New York. Hearst, M. (2000). Next Generation Web Search: Setting Our Sites. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering

What Is Information Seeking? “a process in which humans purposefully engage in order to change their state of knowledge.” p. 5 “a process driven by human’s need for information so that they can interact with the environment.” p. 28 “begins with recognition and acceptance of the problem and continues until the problem is resolved or abandoned” p. 49 Marchionini more than just representation, storage and systematic retrieval IS is Information Retrieval with interacitivity just as spreadsheets let us do “what if” analysis. IS let’s us interatively work through infobases

Information Seeking in Context Learning Information Seeking Information Retrieval Browsing Strategy Analytical Strategy

Search Strategies Analytical Browsing careful planning recall of query terms iterative query reformulations examination of results batched Browsing heuristic opportunistic recognizing relevant information interactive (as can be)

Study Findings Few participants deliberately set out to search for new sites Determined the modes of scanning and moves exercised by the participants Recurring Web behavioral patterns that relate people’s browser actions (Web moves) to their browsing/searching context (Web modes) Modes of scanning: Aguilar (1967) & Weick & Daft (1983, 1984) Moves in information seeking behavior: Ellis (1989) & Ellis et. al. (1993, 1997) Quality of Web information was perceived to be “very high” Human sources were still valued most highly Perceived Source Quality Colleagues External “Expert” Reports/Studies Web Frequency of Source Use Radio/TV Perceived Source Accessibility Managers Source Access: So what does this mean? We find evidence that people use the Web frequently, not because of its perceived quality or accessibility, but because its presumed by users to be a source that actually does contain the information desired OR users have no choice but to use the WWW to seek information (they need information that is not reasonably attainable from any other info source) Interestingly - Didn’t search for new sites sites visited were recommended by other sources or simply stumbled upon

Modes of Scanning

Information Seeking Behaviors & Web Moves 3

Integrated Modes & Moves Model Log files cleaned and formatted Undirected Viewing: This is when users scan broadly. We can expect many instances of starting & chaining(identifying sources of interest & following links from these starting pages) in this phase. Conditioned Viewing:This is when users focus on pre-selected sources. We can expect many instances of browsing (scanning top level pages, site maps), differentiating (selecting useful pages, bookmarking, printing), and monitoring (receiving site updates or revisting sites of interest). Informal Search: This is when users conduct “good enough” searching. We can expect differentiating, monitoring, and extracting (systematically searching a site for specific info) to be typical. Formal Search: This is when users conduct systematic, more rigorous searches. We can expect primarily extracting operations with some complementary monitoring activity.

Behavioral Model of Web Use In total, 61 episodes of “significant” information seeking were identified and classified to the modes and moves of information seeking defined earlier. 12 episodes of starting & chaining in the undirected viewing mode (participants started at portal or news sites and followed links they found interesting on those pages) 18 episodes of browsing, differentiating, & monitoring in the conditioned viewing mode (participants selected a bookmarked page/site or entered the URL directly of a site they remembered; printed a page to show others; these pages were browsed for info content that was of interest; people monitored these sites/pages by frequently returning to them) 23 episodes of differentiating and localized extracting, with some monitoring in the informal search mode (participants went directly to sites they knew to search for info, usually use local search engines; some participants frequented specific sites to perform informal searches) 8 episodes of extracting in the formal search mode (participants systematically worked through a number of search engines or meta search engines to find all important information on a topic; frequent use of search engines) 61 identifiable episodes Confirmed in Interviews

Interview Highlights Most useful work-related sites: Resource sites by associations & user groups News sites Company sites Search engines Most people do not avidly search for new Web sites Criteria to bookmark a site is largely based on a site’s ability to provide relevant & up-to-date information Methods for identifying new Web sites: Magazines & newsletters Other people/colleagues Top 4 types of information sought on the Web: 1) competitive info 2) technical info 3) research info 4) product info

Behavioral Model Highlights People who use the Web engage in 4 complementary modes of information seeking Certain browser based actions & events indicate a particular mode of information seeking Surprises No Explicit Instances of Monitoring to Support Formal Searching Very Few Instances of “Push” Monitoring Extracting Involved Basic Search Strategies Only

IA Model Checklist

Design Recommendations for IA Undirected viewing: starting and chaining Introduce systems that search/recommend jump sites Design portals (home pages) to support undirected, serendipitous viewing Conditioned viewing: browsing, differentiating monitoring Train users to evaluate and escalate priority or importance of info Provide ways of telling users about new content on Web pages Informal search: differentiating monitoring, extracting Pre-select sources & search engines for quick, informal searches Prepackage search strategies developed by subject matter experts Formal search: extracting Use multiple info sources for comprehensive searching Show users how to use advanced search techniques

Tauscher & Greenberg (1997) Mostly Re-Visits (58%) Continually Visit New Pages Access Only A Few Pages Frequently Clusters (Sets) & Short Paths of URLs Frequency Recency “Distance” Types of Navigation Hub and Spoke Depth Searching (lots of links before returning, if at all) Guided Tour (Tasks)

Tauscher & Greenberg (1997)2 Back Button Use Affects Everything (Even More Since Study) Navigation Methods Differ Reasons for Revisiting Explore Further Use Feature (Search or Home Page) “On the Way” to another Page (IA Problem) Users Don’t Understand Browser History Very Well or Do They Misunderstand Page/Site Navigation? Provide Navigation Support Work with the Back Button – Don’t Break its Functionality

Maglio & Barrett (1996) What Do People Do When They Search? Cognition Mental Maps Mental Models (Task Conceptualization) Build Agents Through Understanding IA Take Advantage of Understanding Small Dataset with Specific Searches

Maglio & Barrett (1996) pt 2 Participants Conceptualize Searching as Standard Routines Misremembered Searches Favorite Search Sites Participants Remember Only Key Nodes From a Search Pages as Waypoints (Landmarks) Page Elements Bad News for IA? Predictable Use (Patterns Can Be Perfected in Testing) Imperfect Memory (Use New Mnemonics – Graphics & Text) Leverage Waypoints (Easier to Find Again and Use)

Navigation Systems & IA Layout Global Navigation (Toolbars or Nav bars) Local Navigation (Sidebars or Link Sets) Content Navigation (Intra Site Links?) Relational Navigation (Inter Site Links?) Mechanisms Toolbars, Nav bars, Sidebars Menus, Interactivity (Javascript, Flash, +) Sitemaps (Indexes (A-Z), Task, Guides or Content) Lists (Big and Small, Broad and Focused) Graphics (Logos, ImageMaps, Dynamic Data) Text (Descriptive, Prescriptive, Content) Too Much vs. Too Little (of any combination)

Navigation & Browser (no IA?) Browser Indicators Buttons Bookmarks - Titles URLs History Use List - Titles Menu (Go or Window) Visualization Why Browse When You Can Search? Memorize URLs vs. “Google it” “Social Navigation” (Wear Paths & Popularity) Your Behaviors and Results Sets Personalization

Navigation and Use The Best Design is not Always the Most Usable Redundancy in Design Graphics Links Page Titles Button Names Topic & Heading Titles Users Should Immediately Understand Where They are and Where to Go

Instone’s Navigation Stress Test Random Page is Chosen Find the Chosen Page in Relation to Site Hierarchy (Where in the site?) Purpose What is it doing on this site? Is this the main task of the site? Interface How can I get back to the chosen page? How can I understand it in relation to other pages? Graphics (Who is the page for?) Decide Where Page Links To Associated Pages Part of a Content Unit Part of a Task

Search Systems & IA Rosenfeld – Don’t Build-in Search? Search vs. Browse? Conflict in Design should be Complement in Design? Good Search Makes Up For Bad IA? Search and Browse Percentages? New Users (to Site) New Users (to Web) Advanced Users Who Will Need What Functionality?

Designing Search Systems Indexing Markup Languages & Other Attributes Metadata Content (All, Some, New, Newer?) Functionality Boolean Augment with Context Personalization (Simple to Complex) Interface (p 149-175) Search Boxes, Buttons & “Query Builders” Sorting and Ranking & Hierarchy (Metadata) Results (Abstracting, Gisting(ML), Selection, Keywords) Functions (More Like This, None Like This,

Browsing & Searching (Now) Should Users Always Know Where They Are? Should Users Always Understand Searching (Terms, Operators and Depth)? How Can You Leverage Conventions to Make Browsing Easier? Combinations of Elements Hierarchies Classification How Can IA Augment Basic Searching? Context on the Page Individual Pages Search Results Repetition from other Sites