1 / 35

The Web Changes Everything

The Web Changes Everything. Jaime Teevan, Microsoft Research, @ jteevan. The Web Changes Everything. Content Changes. January February March April May June July August September. Today’s tools focus on the present. But there’s so much more information available!.

ursula
Download Presentation

The Web Changes Everything

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. The WebChanges Everything Jaime Teevan, Microsoft Research, @jteevan

  2. The Web Changes Everything Content Changes January February March April May June July August September

  3. Today’s tools focus on the present But there’s so much more information available! The Web Changes Everything Content Changes January February March April May June July August September January February March April May June July August September People Revisit

  4. The Web Changes Everything Content Changes January February March April May June July August September • Large scale Web crawl over time • Revisited pages • 55,000 pages crawled hourly for 18+ months • Judged pages (relevance to a query) • 6 million pages crawled every two days for 6 months

  5. Measuring Web Page Change • Summary metrics • Number of changes • Time between changes • Amount of change Top level pages change by more and faster than pages with long URLS. .edu and .gov pages do not change by very much or very often News pages change quickly, but not as drastically as other types of pages

  6. Measuring Web Page Change • Summary metrics • Number of changes • Time between changes • Amount of change • Change curves • Fixed starting point • Measure similarity over different time intervals Knot point

  7. Measuring Within-Page Change • DOM structure changes • Term use changes • Divergence from norm • cookbooks • frightfully • merrymaking • ingredient • latkes • Staying power in page Sep. Oct. Nov. Dec. Time

  8. Accounting for Web Dynamics • Avoid problems caused by change • Caching, archiving, crawling • Use change to our advantage • Ranking • Match term’s staying power to query intent • Snippet generation Tom Bosley - Wikipedia, the free encyclopedia Thomas Edward "Tom" Bosley(October 1, 1927 October 19, 2010) was an American actor, best known for portraying Howard Cunningham on the long-running ABC sitcom Happy Days. Bosleywas born in Chicago, the son of Dora and Benjamin Bosley. en.wikipedia.org/wiki/tom_bosley Tom Bosley - Wikipedia, the free encyclopedia Bosleydied at 4:00 a.m. of heart failure on October 19, 2010, at a hospital near his home in Palm Springs, California. … His agent, Sheryl Abrams, said Bosleyhad been battling lung cancer. en.wikipedia.org/wiki/tom_bosley

  9. Revisitation on the Web • Revisitation patterns • Log analysis • Browser logs for revisitation • Query logs for re-finding • User survey for intent Content Changes January February March April May June July August September January February March April May June July August September People Revisit What’s the last Web page you visited?

  10. Measuring Revisitation • Summary metrics • Unique visitors • Visits/user • Time between visits • Revisitation curves • Revisit interval histogram • Normalized TimeInterval

  11. Four Revisitation Patterns • Fast • Hub-and-spoke • Navigation within site • Hybrid • High quality fast pages • Medium • Popular homepages • Mail and Web applications • Slow • Entry pages, bank pages • Accessed via search engine

  12. Search and Revisitation • Repeat query (33%) • microsoft research • Repeat click (39%) • research.microsoft.com • Query  msr • Lots of repeats (43%) • Many navigational

  13. 7th

  14. How Revisitation and Change Relate Content Changes January February March April May June July August September January February March April May June July August September People Revisit Why did you revisit the last Web page you did?

  15. Possible Relationships • Interested in change • Monitor • Effect change • Transact • Change unimportant • Find • Change can interfere • Re-find

  16. Understanding the Relationship • Compare summary metrics • Revisits: Unique visitors, visits/user, interval • Change: Number, interval, similarity

  17. Comparing Change and Revisit Curves • Three pages • New York Times • Woot.com • Costco • Similar change patterns • Different revisitation • NYT: Fast (news, forums) • Woot: Medium • Costco: Slow (retail)

  18. Comparing Change and Revisit Curves • Three pages • New York Times • Woot.com • Costco • Similar change patterns • Different revisitation • NYT: Fast (news, forums) • Woot: Medium • Costco: Slow (retail) Time

  19. Within-Page Relationship • Page elements change at different rates • Pages revisited at different rates • Resonance can serve as a filter for interesting content

  20. Exposing Change Diff-IE toolbar Changes to page since your last visit

  21. Interesting Features New to you Always on Non-intrusive In-situ

  22. Studying Diff-IE Content Changes January February March April May June July August September SURVEY How often do pages change? o oooo How often do you revisit? o oooo SURVEY How often do pages change? o oooo How often do you revisit? o oooo Install Diff-IE January February March April May June July August September People Revisit

  23. Seeing Change Changes Web Use • Changes to perception • Diff-IE users become more likely to notice change • Provide better estimates of how often content changes • Changes to behavior • Diff-IE users start to revisit more • Revisited pages more likely to have changed • Changes viewed are bigger changes • Content gains value when history is exposed 14% 51% 53%

  24. Change Can Cause Problems • Dynamic menus • Put commonly used items at top • Slows menu item access • Search result change • Results change regularly • Inhibits re-finding • Fewer repeat clicks • Slower time to click

  25. Change During a Single Query • Results even change as you interact with them

  26. Change During a Single Query • Results even change as you interact with them • Many reasons for change • Intentional to improve ranking • General instability • Analyze behavior when people return after clicking

  27. Understanding When Change Hurts • Metrics • Abandonment • Satisfaction • Click position • Time to click • Mixed impact • Results change Above: 4.5% increase • Results change Below: 1.9% decrease

  28. Use Experience to Bias Presentation

  29. Change Blind Search Experience

  30. The Web Changes Everything Content Changes Web content changes provide valuable insight January February March April May June July August September Relating revisitation and change enables us to • Identify pages for which change is important • Identify interesting components within a page January February March April May June July August September People revisit and re-find Web content Explicit support for Web dynamics can impact how people use and understand the Web People Revisit

  31. Thank you. Jaime Teevan @jteevan Web Content Change Adar, Teevan, Dumais &Elsas. The Web changes everything: Understanding the dynamics of Web content. WSDM 2009. Kulkarni, Teevan, Svore & Dumais. Understanding temporal query dynamics. WSDM 2011. Svore, Teevan, Dumais & Kulkarni. Creating temporally dynamic Web search snippets. SIGIR 2012. Web Page Revisitation Teevan, Adar, Jones & Potts. Information re-retrieval: Repeat queries in Yahoo’s logs. SIGIR 2007. Adar, Teevan & Dumais. Large scale analysis of Web revisitation patterns. CHI 2008. Tyler & Teevan. Large scale query log analysis of re-finding. WSDM 2010. Teevan, Liebling & Ravichandran. Understanding and predicting personal navigation. WSDM 2011. Relating Change and Revisitation Adar, Teevan & Dumais. Resonance on the Web: Web dynamics and revisitation patterns. CHI 2009. Teevan, Dumais, Liebling & Hughes. Changing how people view changes on the Web. UIST 2009. Teevan, Dumais & Liebling. A longitudinal study of how highlighting Web content change affects people’s web interactions. CHI 2010. Lee, Teevan & de la Chica. Characterizing multi-click behavior and the risks and opportunities of changing results during use. SIGIR 2014.

More Related