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Jacek GwizdkaDepartment of Library and Information Science
Rutgers University
Sunday, Oct 09, 2011
Panel: Social Tagging and Folksonomies:
Indexing, Retrievingand Beyond?
Searching and browsing via tag clouds
CONTACT:
www.jsg.tel
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Process of Tagging
Users associate tags with web resources
Tags serve in social, structural, and semantic role structural role: starting points for navigation; helping users to orient themselves
semantic role: description of a set of associated resources
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Tag Clouds
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My Claims
Tag Clouds help in information search
by saving searchers effort
Tag Clouds do not support browsing tasks
do not show relationships and do not show history
Not just claims
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Research Question
Do tag clouds benefit users in search tasks?
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User Interface with Overview Tag Cloud
Our retrieval system populated with data from delicious 6
List UI
Overview Tag
Cloud UI
Search Result List Tag Cloud
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User Actions in Two Interfaces
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ViewSearchResults
Viewone result
page
Start
End
Delete TagNew Tag
ClickResult
URLClickBack
button Click Done &enter answer
1. List
2.Overview
Tag Cloud
click
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Experiment Design
37 participants
Working memory assessed using memory span task (Francis & Neath 2003)
Within subject design with 2 factors: task and user interface
Tasks
everyday information search (e.g., travel, shopping) at two levels of task
complexity
Four task rotations for each of two user interfaces
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Fact finding
Information
gathering Fact finding
Information
gathering
Fact findingInformation
gathering
Information
gatheringFact finding
Information
gatheringFact finding Fact finding
Information
gathering
Information
gatheringFact finding
Information
gatheringFact finding
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Measures
Task completion time
Cognitive effort:
from mouse clicks: user decisions expressed as user selection of
search terms = number of queries, opening documents to view from eye-tracking reading effort measures: (based on intermediate
reading model) scanning vs. reading; length of reading sequences;
reading fixation duration, number of regression fixations in reading
sequence, spacing of fixations in reading sequence.
Task outcome = relevance * completeness
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Results
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Results : Time and User Behavior
Overview Tag Cloud+ Listmade users faster and more efficient
less time on task: 191s inOverview+List vs. 261s in List UI
less queries: 7 inOverview+List vs. 8.3 in List UI
no significant differences in task outcomes
Overview Tag Cloudfacilitated formulation of more effective queries
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Results : Cognitive Effort
Overview Tag Cloud + List required less effort, higher efficiency
less fixations (total and mean reading seq len) more efficient
less regressions less difficulty in reading
12List Overview Tag Cloud + List
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Results : Cognitive Effort
Overview Tag Cloud + List required less effort, higher efficiency
less fixations (total and mean reading seq len) more efficient
less regressions less difficulty in reading
Comparing onlyresults list region in two UI conditions
less effort invested in results list in Overview Tag Cloud + List
Overview Tag Cloudhelped to lower cognitive demands
13List Overview Tag Cloud + List
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Did Tag Cloud Help All Users?
No there are individual differences
Two users, same UI and same task 14
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Is Tag Cloud Helpful?
Yes!
OverviewTag Cloud+ ListUI
made people faster and required less effort
also reflected in a number of eye-tracking measures
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Browsing large sets of tagged documents
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An Example of Browsing (CiteULike)
A typical model of browsing with tag clouds:
Pivot browsing: a lightweight navigation mechanism
1. information 2. retrieval 3. algorithms 4. phylogeny
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Is There a Problem?
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Users ConceptualizationsThe labyrinth
being lost
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The journey
switching
directionand being stack
The space
increasingdistance,
and continuity18 participants
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Whats the Problem?
Users
feel lost
experience switching, yet expect some continuity
In Pivot Browsing each step is treated as a separate move
View is re-oriented - New list of documents along with their tags
At each step context is switched
Relationships between steps are not shown
e.g., overlap between tag clouds not indicated
Pivot browsing seems to be notlightweight
conceptualizing multiple tags assigned in different quantities to different
documents is difficult
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Research Questions
How can we support continuity in tag-space browsing?
How can we promote better understanding
of tag-document relationships (sensemaking)?
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Recall: Example of Navigation (CiteULike)
1. information 2. retrieval 3. algorithms 4. phylogeny
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User Interface with History tag clouds (Tag Trails)
Supporting continuity in tag-space navigation by providing history
information retrieval algorithms phylogeny
History
tag clouds
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User Interface with Heat map (Tag Trails 2)
Supporting continuity in tag-space navigation by providing history and
making (some) relationships (more) explicit
Tag cloud
Results list
Column-tags: most recently
visited tags
from left to right
Row-tags: selection ofmost frequent tags
Cells color-codedaccording to tags df
Heat map
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Summary & Conclusions
Tagging metadata for free: does the effort pay off?
Yes, but not for all tasks
Tag clouds
helpful in search tasks
but to support browsing new presentations of tags needed
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Thank you! Questions?
Jacek Gwizdka | contact: http://jsg.tel
Related publications:
Gwizdka, J. (2009a). What a difference a tag cloud makes: Effects of tasks and cognitive abilities on
search results interface use. Information Research, 14(4), paper 414. Available online at
Gwizdka, J. (2010c). Of kings, traffic signs and flowers: Exploring navigation of tagged documents. In
Proceedings of Hypertext2010 (pp. 167-172). ACM Press.
Gwizdka, J. & Bakelaar, P. (2009a). Tag trails: Navigating with context and history. CHI 09 extended
abstracts (pp. 4579-4584). ACM Press.
Gwizdka, J. & Bakelaar, P. (2009b). Navigating one million tags. Short paper and poster presented at
ASIS&T2009, Vancouver, BC, Canada.
Cole, M.J. & Gwizdka, J. (2008). Tagging semantics: Investigations with WordNet. Proceedings of
JCDL2008. ACM Press.
Gwizdka, J. & Cole, M.J. (2007). Finding it on Google, finding it on del.icio.us. In L. Kovcs, N. Fuhr, &
C. Meghini (Eds.), Lecture notes in computer science (LNCS): Vol. 4765. Research and advanced
technology for digital libraries, ECDL2007. (pp. 559-562). Springer-V
erlag
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Extra Slides
Intro to Reading model
Tag cloud examples
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Introducing Reading Model
Scanning fixations provide some semantic information
limited to foveal visual field (1r visual acuity) (Rayner & Fischer, 1996)
Reading fixation sequences provide more information than
isolated scanning fixations
information is gained from the larger parafoveal region (5r beyond foveal focus;asymmetrical, in dir of reading) (Rayner et al., 2003)
some types of semantic information is available only through reading
sequences
We implemented the E-Z Reader reading model (Reichle et al., 2006)
Lexical fixations duration >113 ms (Reingold & Rayner, 2006)
Each lexical fixation is classified to Scanning or Reading (S,R)
These sequences used to create a two-state model
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ReadingModel States and Characteristics
Two states: transition probabilities
Number of lexical fixations and duration
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Example Reading Sequence
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Tag Clouds Everywhere!
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