Impact of Highlighting Change on Web Interactions
This study explores the effects of highlighting changes on people's web interactions, emphasizing the frequency of content changes and the significant role of revisitation behavior. It discusses how web dynamics, content modifications, and systems that expose web changes influence online user experiences. The research highlights the importance of understanding how changes in web content affect user engagement and behavior.
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Presentation Transcript
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 Studies of content change [Adar et al., Fetterly et al.] Web doubles and half the pages change yearly Frequency and degree of change characterized
Web Dynamics People revisit Web pages frequently Content Changes Half of visits are revisits[Adar et al., Tauscher&Greenberg] A third of searches are for re-finding [Teevan et al.] 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 January February March April May June July August September People Revisit
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
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
DiffIE New to you Always on Non-intrusive In-situ Changes to page since your last visit
SURVEY How often do pages change? o o o o o SURVEY How often do pages change? o o o o o 30 people install DiffIE Studying DiffIE How often do you revisit? o o o o o How often do you revisit? o o o o o 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 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
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%
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+%
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 Pages with product information Wikipedia pages Company homepages Personal home pages of people you know Reference pages (dictionaries, yellow pages, maps) Change a lot Change little
Affects of Highlighting Change People revisit Web pages more The pages revisited change more Perceptions of change are reinforced
Thank you. Jaime Teevan http://research.microsoft.com/~teevan 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 people view 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).
