Understanding Web Searching

1
Understanding Web Searching

• Secondary Readings and So On
• Will Meurer for WIRED
• October 7, 2004

2
Introduction

• Why do we care about how people use the Web?
• Todays topics (10/7, not the present age)
• Implicit vs. explicit feedback
• Representation effectiveness
• Browser-based activities
• History mechanisms
• How do we cater to the people?
• Resources
• Research

3
Implicit vs. Explicit FeedbackReading Time,
Scrolling and (Kelly Belkin, 2001)

• Implicit feedback (Morita Shinoda)
• Time spent on a page is directly related to user
  interest. Backed by many studies.
  
• Explicit feedback (this study)
• Time spent on a page is similar for relevant and
  irrelevant content.
  
• Results suggest
• Generalizability is severely affected by
  explicit feedback methods.
  
• Spend time to choose the right feedback type!

4
Implicit vs. Explicit FeedbackReading Time,
Scrolling and (Kelly Belkin, 2001)

• Why do the results differ?
• Relevance was difficult to distinguish this time
• Participants are truly interested in the content
  former studies
  
• Users may have rushed to complete in this
  experimental context

5
Representation Effectiveness How we really use
the Web (Krug, 2000)

• Three facts of life
• We dont read pages. We scan them.
• Why? hurry, necessity, habit
• If we are to read its entirety, we save or
  print!
  
• (ClearType project)

6
Representation Effectiveness How we really use
the Web (Krug, 2000)

• We dont make optimal choices. We Satisfice.
• Why? hurry, quick access to and fro, less work
  than thinking
  
• Generally, its more productive to guess.

7
Representation EffectivenessHow we really use
the Web (Krug, 2000)

• We dont figure out how things work.
• Why? not important, if it aint broke
  (baroque)
  
• Is it important to us whether the user
  understands how it works or not? Why?

8
Representation EffectivenessCognitive Strategies
in Web (Navarro-Prieto, et al, 1999)

• Users get lost on the Web. Why?
• It is not just interactivity between user and
  system, rather user, task, and information
  
• Analysis structure of browsing behavior presented
  and tested
  
• The Interactivity Framework or How we should
  analyze cognitive strategies

9
Representation EffectivenessCognitive Strategies
in Web (Navarro-Prieto, et al, 1999)

• The Interactivity Framework
• User Level Web experience, cognitive processes,
  cognitive style, knowledge (CS majors knew more
  about SE processes)
  
• User Strategies based on searching structure
  (or lack of), task nature

10
Representation EffectivenessCognitive Strategies
in Web (Navarro-Prieto, et al, 1999)

• Information Structure
• Internal (users) representation
• External (systems) representation
• Computational Offloading How much work does the
  user have to do to understand and how much does a
  representation help?
  
• Re-representation How much it makes problem
  solving easier or more difficult
  
• Graphical Constraining How it constrains
  inferences
  
• Temporal and Spatial Constraining How it helps
  when distributed over time and space

11
Representation EffectivenessCognitive Strategies
in Web (Navarro-Prieto, et al, 1999)

12
Representation EffectivenessCognitive Strategies
in Web (Navarro-Prieto, et al, 1999)

• More Results
• Experienced users searched with a plan
• By having a plan you keep a more internal
  representation and focus your search
  
• Inexperienced users were more influenced by
  external representations
  
• Computational Offloading Results
• Must explain
• How have these issues changed?

13
Representation Effectiveness Cognitive
Strategies in Web (Navarro-Prieto, et al, 1999)

• Conclusions
• Cognitive strategies used by the participants
  depend on how the information is structured.
  
• Interaction is a multi-dimensioned concept.
• Search engine interfaces should be designed to
  have less restrictive external representation.

14
Browser-based ActivitiesCharacterizing Browsing
(Catledge Pitkow, 1995)

• User study of browsing events at the Georgia Tech
  (xMosaic browser)
  
• Three main browsing strategies identified
• Search browsing directed search, goal known
• General purpose browsing consulting highly
  likely sources for needed information
  (dictionary.com)
  
• Serendipitous browsing random
• Most people use a combination of these

15
Browser-based ActivitiesCharacterizing Browsing
(Catledge Pitkow, 1995)

• Results
• Users were patient 99 of the time for long page
  loads
  
• 1222 unique sites accessed outside of GATech
  (16 of Web servers)
  
• Paths were calculated (sequences of page
  navigation)
  
• Per session, paths of 7 different sites occurred
  5 times
  
• Per user, paths of 8 different sites occurred 9
  times

16
Browser-based ActivitiesCharacterizing Browsing
(Catledge Pitkow, 1995)

• More Results
• 2 of the retrieved pages were saved or printed
• Based on users slope, browsing strategy
  categories were applied
  
• Slope can also categorize usage
• patterns of Web documents
• Users tended to operate in one
• small area of a site

17
Browser-based Activities Characterizing
Browsing (Catledge Pitkow, 1995)

• Design Strategies
• Users averaged 10 pages per server
• Make most important info within 2 or 3 jumps from
  the index
  
• Do not put too many links on one page increases
  search time (back, forward, back, site map,
  etc.)
  
• Facilitate the likely visitor browser patterns
• Maybe make more than one version of your page?
• Most work well in a hub and spoke environment
• The Future
• Offer site tour based on most frequently traveled
  paths
  
• Alter page design dynamically based on site trends

18
History Mechanisms (in browsers)Revisitation
Patterns in (Tauscher Greenberg, 1997)

• Purpose Provide empirical data to aid in the
  development of effective history mechanisms
  
• Understand revisitation patterns
• Evaluate current mechanisms and suggest best
  practices and methods
  
• Data Collection
• Altered version of xMosaic to record activity
• Survey of users afterward

19
History Mechanisms (in browsers)Revisitation
Patterns in (Tauscher Greenberg, 1997)

• Revisitation Results
• 58 recurrence rate (40 are new pages!)
• As people search they build their vocabulary
• 7 browsing strategies
• First-time visits to cluster of pages
• Revisits to pages
• Authoring of pages (high reload percentage)
• Regular use of web-based apps
• Hub-and-spoke (breadth-first approach)
• Guided tour (e.g. next page links)
• Depth-first search (following links deeply before
  returning to the index)

20
History Mechanisms (in browsers)Revisitation
Patterns in (Tauscher Greenberg, 1997)

• Revisitation Results
• Visit frequency as a function of distance
• Users mostly revisit recently visited pages
  (within about 6 jumps)
  
• 39 chance that the next URL will match one of
  the previous 6 pages visited
  
• Access frequency
• 60 of pages visited only once
• 19 visited twice
• 8 visited 3 times
• 4 visited 4 times
• Locality (not valuable for predicting next page)
• Most locality sets were small
• Only 2.5 to 4.5 URLs per set
• Only 15 of pages were part of a locality set
• Paths (not valuable for predicting next page)
• Could these be captured and offered in a history
  mechanism?
  
• Time per page could indicate path

21
History Mechanisms (in browsers)Revisitation
Patterns in (Tauscher Greenberg, 1997)

• Mechanism types
• Recency Ordered
• Sequential order based on time accessed
• Repeated entries for revisitation
• Pruned by keeping only first instance or only
  last
  
• Simple for users to understand (they remember
  paths)
  
• Frequency Ordered
• Most visited at top, least visited at bottom
• User interest changes, latest URLs must have
  frequency
  
• How to break ties last visited, earliest
  visited
  
• When few items are on the list, this suffers
• Difficult for users to understand

22
History Mechanisms (in browsers)Revisitation
Patterns in (Tauscher Greenberg, 1997)

• Stack-based
• Recently visited at top
• Order and availability depend on
• Loading causes page to be added to the top
• Recalling changes pointer to the currently
  displayed page
  
• Revisiting user reloads the page, has no effect
  on the stack
  
• Keeps duplicates
• Non-persistent vs. persistent (btw sessions)
• Better than recency at short distances
• Users have difficulty understanding this model

23
History Mechanisms (in browsers)Revisitation
Patterns in (Tauscher Greenberg, 1997)

• Hierarchically Structured
• Recency ordered hyperlink sublists
• Like recency w/ latest position saved
• Each URL has its own sublist of links from that
  page
  
• Helps with common linking paths
• Easier to understand
• Context-sensitive web subspace
• Somewhat of a combination of the above-mentioned
  and stack-based approaches
  
• Gives user better understanding of context of
  his/her searches
  
• May be difficult to remember where a certain URL
  was
  
• I THINK this approach would be a great tool

24
History Mechanisms (in browsers)Revisitation
Patterns in (Tauscher Greenberg, 1997)

• Do users actually use history mechanisms?
• Less than 1 of navigation
• 3 involve favorites
• 30 of navigation was back button usage

25
How do we cater to the people?

• Inter-site browsing strategies are not easy to
  tackle. How would you control that?
  
• Why should we attempt to understand user behavior
  and search strategies?
  
• Formulate general design principles (e.g. 3 level
  depth)
  
• Design for multiple searching personalities
• Understand how to survey your intended users or
  get feedback most appropriately
  
• Identify importance of all aspects of the
  development process and allocate resources
  accordingly

26
How do we cater to the people?

• Some Bright Ideas
• Personalized search
• Learning systems You might also like
• www.a9.com (history, favorites, personalized
  interface)
  
• But what about changing for different types of
  user behavior based on the users path history on
  your server?
  
• Researched since 1995 and earlier!
• What has resulted?
• Microsoft ASP.net 2.0 Web Parts

27
What resources are out there?

• xMosaic 2.6 download, for those of you so
  excited
  
• Architecture of the World Wide Web
  http//www.w3.org/TR/webarch/
  
• Sum Sun Sug Gestions http//www.sun.com/980713/web
  writing/
  
• Jakob Nielsen research on content usability,
  http//useit.com/alertbox/9710a.html
  

28
Research

• Vox Populi The Public Searching Of The Web
  (2001)
  
• Compares statistics from two studies
• Shows how public searching changed from 1997 to
  1999
  
• Usage Patterns of a Web-Based Library Catalog
  (2001), Michael D. Cooper
  
• Real Life, Real Users, and Real Needs A Study
  and Analysis of User Queries on the Web (2000),
  Jansen, Spink Saracevic
  
• Redefining the Browser History in Hypertext Terms
  (), Mark Ollerenshaw