DiffIE: Changing How You
View Changes on the Web
Jaime Teevan, Susan T. Dumais,
Daniel J. Liebling, and Richard L. Hughes
Microsoft Research
Information
Artifacts Change
Digital Dynamics Easy to Capture
Web Dynamics
Content Changes
January
February
March
April
May
June
July
August
September
• Number of studies of change [2, 7, 10, 20]
• Frequency and degree of change characterized
• Visited pages are more likely to change [2]
Web Dynamics
• People revisit on the Web a lot
Content Changes
– Over half of page visits are revisits [2, 22]
– Over a third of searches are for re-finding [23]
• Revisitation relates to change
January
February
March
April
May
June
July
August
– 66% of revisits are to changed pages [2]
– 20% of the content changes [2]
– Revisiting often motivated by change [2, 15]
People –
Revisit
Change interferes with revisiting [21, 23]
January
February
March
April
May
June
July
August
September
September
Web Dynamics
Content Changes
January
February
March
April
May
June
July
August
September
January
February
March
April
May
June
July
August
September
People Revisit
Today’s Browse and Search Experiences
Ignores …
DiffIE toolbar
DiffIE
Changes to page
since your last visit
Systems That Expose Web Change
• Historical access to pages
– Internet Archives (archive.org)
• Subscription to change
– RSS, Web slices
– Monitoring support [15]
• In-situ awareness of change
–
symbols
– Dynamo [3], Difference Engine [9], WebCQ [17]
Interesting Features of DiffIE
New to you
Always on
Non-intrusive
In-situ
Overview
•
•
•
•
How DiffIE works
How we studied DiffIE
How DiffIE is used
Conclusions and future work
HOW DiffIE WORKS
DiffIE Architecture
Toolbar Component
Web
IE
Comparison Component
DiffIE
Client Machine
Cache
Toolbar
Feedback
buttons
Status message
Hide highlighting
Compare to
older versions
See previous
version
Cache
• Web page representation
– Leaf nodes in DOM: Hash of text
– Parent nodes: Hash of children, appended
• Cache multiple versions of pages visited
• Small footprint (50KB)
– Exact duplicates stored as pointer files
– Cap count (only 6% of pages visited >5 times)
• Privacy preserving
Comparison Component
•
•
•
•
Change Node has same children, child changes
Deletion Node has fewer children
Addition Node has more children, child new
Movement Node has new child, child present
A
B
A
C
D
B
E
D
C
D
E
EF
Comparison Component
•
•
•
•
•
•
Change Node has same children, child changes
Deletion Node has fewer children
Addition Node has more children, child new
Movement Node has new child, child present
Highlighted: Additions, changes
Not highlighted: Moves, deletions
STUDYING DiffIE
Interesting Features of DiffIE
New to you
Always on
Background
In-situ
Methods for Studying DiffIE
• Large scale demonstration
• Feedback buttons
• Experience interview
– 11 people (5 female, 6 male)
– Interviewed after extended DiffIE use (2+ weeks)
– Asked about general experience
– Revisited 10 pages (half from today/yesterday)
HOW DiffIE IS USED
Expected New Content
Monitor
Unexpected Important Content
Serendipitous Encounters
Understand Page Dynamics
Attend to Activity
Edit
Unexpected
Expected
Unexpected
Important Content
Edit
Expected
New Content
Attend to Activity
Understand
Page Dynamics
Monitor
Serendipitous
Encounter
Monitor
Find Expected New Content
CONCLUSION AND FUTURE WORK
Summary
• Web dynamics important
– Change and revisitation common and related
• DiffIE exposes change upon revisitation
– Caches representations of visited pages
– Additions and changes identified and highlighted
• DiffIE used in unexpected ways
– Some Web content becomes more valuable
– Not as useful for sites designed around change
Next Steps
• Additional ways to display change
– Other interfaces: fade, moves/deletes, differences
– Just show change: mobile, mash ups
– Allow user to subscribe to change
• Decide when and what to highlight
– Important v. unimportant changes (e.g., ads)
– Provide access to unseen change
• API exposing change
Thank you.
Jaime Teevan
http://research.microsoft.com/~teevan
DiffIE Teevan, J., S. T. Dumais, D. J. Liebling, and R. Hughes. Changing How People
View Changes on the Web. UIST 2009.
Change Adar, E., J. Teevan, S. T. Dumais, and J. L. Elsas. The Web changes everything:
Understanding the dynamics of Web Content. WSDM 2009 (Best Student Paper).
Revisitation Adar, E., J. Teevan, and S. T. Dumais. Large scale analysis of Web
revisitation patterns. CHI 2008 (Best Paper).
Relationship Adar, E., J. Teevan, and S. T. Dumais. Resonance on the Web: Web
dynamics and revisitation patterns. CHI 2009.
EXTRA SLIDES
DiffIE Received Positively
• Feedback buttons
– 51% of unsolicited feedback positive (v. 10-25%)
• Experience interview (conditioned on change)
– 61% positive
– 18% neutral
– 21% negative
Reported Experience with DiffIE
Nothing highlighted
Too much highlighted
Unexpected highlighting
… that was important
… that was interesting
… that was distracting
Never
Rarely
Sometimes
Often
Always
Performance
•
•
•
•
•
Highlighting shown on page load event
Appears 10s to 100s of milliseconds after load
Does not interfere with browsing experience
Often appears after interaction begins
Notification of delay important