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How Highlighting Change Affects People’s Web Interactions

How Highlighting Change Affects People’s Web Interactions. Jaime Teevan, Susan Dumais & Dan Liebling Microsoft Research. Web Dynamics. Content Changes. January February March April May June July August September.

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How Highlighting Change Affects People’s Web Interactions

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  1. How Highlighting Change Affects People’s Web Interactions Jaime Teevan, Susan Dumais & Dan Liebling Microsoft Research

  2. Web Dynamics Content Changes January February March April May June July August September • Studies of content change [Adar et al., Fetterly et al.] • Web doubles and half the pages change yearly • Frequency and degree of change characterized

  3. January February March April May June July August September People Revisit Web Dynamics • People revisit Web pages frequently • Half of visits are revisits[Adar et al., Tauscher&Greenberg] • A third of searches are for re-finding [Teevan et al.] Content Changes • Revisitation relates to change • 66% of revisits are to changed pages [Adar et al.] • 20% of the content changes [Adar et al.] • Often motivated by change [Adar et al., Keller et al.] • Change can cause problems [Obendorf et al., Teevan et al.] January February March April May June July August September

  4. January February March April May June July August September People Revisit Today’s Browse and Search Experiences Ignores … Web Dynamics Content Changes January February March April May June July August September

  5. Systems That Expose Web Change • Historical access to Web pages • Internet Archives (archive.org) • Subscription to Web content change • RSS, Web slices • Monitoring support [Kellar et al.] • In-situ awareness of Web content change • symbols • Dynamo, Difference Engine, WebCQ new

  6. DiffIE New to you Always on Non-intrusive In-situ Changes to page since your last visit

  7. April 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 People Revisit Studying DiffIE SURVEY How often do pages change? o oooo How often do you revisit? o oooo 30 people install DiffIE SURVEY How often do pages change? o oooo How often do you revisit? o oooo Content Changes April 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

  8. People Revisit More • Perception of revisitation remains constant • How often do you revisit? • How often are revisits to view new content? • Actual revisitation increases • First week: 39.4% of visits are revisits • Last week: 45.0% of visits are revisits • Why do people revisit more? 14%

  9. Revisited Pages Change More • Perception of change increases • What proportion of pages change regularly? • How often do you notice unexpected change? • Amount of change seen increases • First week: 21.5% revisits changed by 6.2% • Last week: 32.4% revisits changed by 9.5% • Exposed change drives visits to changed pages 8% 17% 51+%

  10. Perceptions of Change Reinforced • Change by page type • Pages that change a lot  change more • Pages that change a little  change less News pages Message boards, forums, news groups Search engine results Blogs you read Change a lot Pages with product information Wikipedia pages Company homepages Personal home pages of people you know Reference pages (dictionaries, yellow pages, maps) Change little

  11. Affects of Highlighting Change • People revisit Web pages more • The pages revisited change more • Perceptions of change are reinforced

  12. Change • Adar, Teevan, Dumais & Elsas. The Web changes everything: Understanding the dynamics of Web Content. WSDM ’09 (Best Student Paper). • Elsas & Dumais. Leveraging temporal dynamics of document content in relevance ranking. WSDM ’10. Revisitation • Adar, Teevan & Dumais. Large scale analysis of Web revisitation patterns.CHI ’08 (Best Paper). • Teevan, Adar, Jones & Potts. Information re-retrieval: Repeat queries in Yahoo’s logs. SIGIR ’07. • Tyler & Teevan. Large scale query log analysis of re-finding. WSDM ’10. Relationship Adar, Teevan & Dumais. Resonance on the Web: Web dynamics and revisitation patterns. CHI ’09. DiffIE • Teevan, Dumais, Liebling & Hughes. Changing how peopleview changes on the Web. UIST ’09. • Teevan, Dumais & Liebling. A longitudinal study of how highlighting Web content change affects people’s Web interactions. CHI ’10 (Best Paper). Thank you. Jaime Teevan http://research.microsoft.com/~teevan

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