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DiffIE: Changing How You View Changes on the Web DiffIE: Changing How You View Changes on the Web Jaime Teevan, Susan T. Dumais, Daniel J. Liebling, and Richard L. Hughes Microsoft Research
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Information Artifacts Change
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Digital Dynamics Easy to Capture
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Web Dynamics JanuaryFebruaryMarch April May JuneJuly August September Content Changes Number of studies of change [2, 7, 10, 20] Frequency and degree of change characterized Visited pages are more likely to change [2]
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Web Dynamics JanuaryFebruaryMarch April May JuneJuly August September Content Changes People Revisit JanuaryFebruaryMarch April May JuneJuly August September People revisit on the Web a lot – Over half of page visits are revisits [2, 22] – Over a third of searches are for re-finding [23] Revisitation relates to change – 66% of revisits are to changed pages [2] – 20% of the content changes [2] – Revisiting often motivated by change [2, 15] – Change interferes with revisiting [21, 23]
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Web Dynamics JanuaryFebruaryMarch April May JuneJuly August September Content Changes People Revisit JanuaryFebruaryMarch April May JuneJuly August September Today’s Browse and Search Experiences Ignores …
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DiffIE Changes to page since your last visit DiffIE toolbar
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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]
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Interesting Features of DiffIE Always on In-situ New to you Non-intrusive
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How DiffIE works How we studied DiffIE How DiffIE is used Conclusions and future work Overview
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HOW DiffIE WORKS
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DiffIE DiffIE Architecture Web Cache Toolbar ComponentComparison Component IE Client Machine
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Toolbar Compare to older versions Status message Feedback buttons See previous version Hide highlighting
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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
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Comparison Component Change Deletion Addition Movement A A B B D D C C E E F F A A B B C C D D E E E E D D Node has fewer children Node has more children, child new Node has new child, child present Node has same children, child changes
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Comparison Component Change Deletion Addition Movement Highlighted: Additions, changes Not highlighted: Moves, deletions Node has fewer children Node has more children, child new Node has new child, child present Node has same children, child changes
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STUDYING DiffIE
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Interesting Features of DiffIE Always on In-situ New to you Background
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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)
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HOW DiffIE IS USED
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Expected New Content
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Monitor
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Unexpected Important Content
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Serendipitous Encounters
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Understand Page Dynamics
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Attend to Activity
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Edit
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Attend to Activity Edit Understand Page Dynamics Serendipitous Encounter Unexpected Important Content Expected New Content Monitor Expected Unexpected
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Monitor
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Find Expected New Content
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CONCLUSION AND FUTURE WORK
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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 Summary
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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
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Thank you. 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. Jaime Teevan http://research.microsoft.com/~teevan
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EXTRA SLIDES
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DiffIE Received Positively Feedback buttons – 51% of unsolicited feedback positive (v. 10-25%) Experience interview (conditioned on change) – 61% positive – 18% neutral – 21% negative
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Reported Experience with DiffIE
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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
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