How Websites Learn: Information Architecture that Adapts to Use

1. How Websites Learn:Information Architecture that Adapts to Use Peter Merholz Work: http://epinions.com Play: http://peterme.com/ http://peterme.com/ia2000/

2. Little Architects

3. A problem: • Increasingly, websites corral massive amounts of information • In fact, a strength of the Web is access to unlimited information • But how to present the information meaningfully?

4. A problem: • Providing a singular, top-down editorial structure isn’t feasible • But nor can you allow a morass like USENET or an unstructured Web

5. Another problem • Web sites don’t respond to use • They’re static, and assume all information is of equal importance

6. Case in point • Productopia, R.I.P. • Dozens or hundreds of employed people are costly

7. A potential solution • Adaptive information architectures • Bottom-up organization based on qualities of the information and how the information is used • Information spaces that metamorphose based on use • Rich information spaces are complex systems, the study of which can inform our designs

8. Structure based on the qualities of the information • Linguistic processing and categorization schemes like Autonomy and Northern Light • Display systems like Self-Organizing Maps (http://websom.hut.fi/websom/), Thinkmap (http://www.thinkmap.com/), Cartia (http://www.cartia.com/)

9. The use is more important than inherent qualities • While the Thing qua Thing is important, • It’s more important how people relate to and interact with that thing • Cognitive scientists have found that people categorize the world not on the inherent qualities of things, but on how they interact with those things. (Women, Fire, and Dangerous Things, Lakoff)

10. So, what does all this mean? • What is an information space that adapts to use? • An obvious and popular example: The Bestseller List • - People are interested in what’s popular

11. Models for social effects • Self-policing • Word of mouth • Footpaths • The Agora

12. Self-policing – Epinions.com • Nearly 700,000 opinions—no editing • Community can • - Rate content • - Trust each other

13. Self-policing—Epinions.com Generic

14. Word of mouth – Information structured through people You tell people about a movie you saw, a book you read, a car you drive Known experts are sought out for their input

15. Word of mouth – aligning yourself with others’ tastes Epinions.com – Other products written about, other opinions worth reading Launch.com – Collaborative filtering Napster – Hot lists

16. Word of Mouth—Epinions.com Generic Personalized

17. Word of Mouth – Google.com • That HREF tag carries a lot of meaning • PageRank – measures importance through linking

18. Footpaths How is the information traversed and used? Take advantage of what people do

19. Footpaths • Designers begin with a form… http://fury.com/berkeleypaths

20. Footpaths • But people will make it their own…

21. Footpaths – Swiki : Icons representing use • http://swiki.sics.se/ • Footprints and Dinosaurs • Explicates what’s there, doesn’t make new connections

22. The King – Amazon.com • People who bought X also bought… • Creates meaningful relationships that can break typical taxonomic bounds • Purchase Circles • Localized Bestseller lists • The Page You Made • Personalized clickstream analysis

23. Amazon’s biggest lesson • Track use passively—don’t expect people will do the work for you

24. The Agora • People in the same place at the same time likely have something in common • Purple-moon.com • H2G2.com

25. A Meta-Web – Everything2.com • A bottom-up network of thought connected by • Hard links – explicit • Soft links – implicit • Ranked by voting • Tiered community • ‘Who’s online’ ….They’ve got it all!

26. Except a sense of purpose, structure, meaning… • Difficult to figure out • Community is double-edged • In an email from Will Sargent: • The downfall of Everything2 (the site, not the architecture) is sadly linked into its quality control. Editors are picked from users who have made significant contributions to the site and have been there for a while. These editors/gods have free license to downvote and nuke as they see fit. So far so good. • The problem is that the editors are not impartial observers. They have been known to downvote nodes which use language which they don't like, political opinions they don't agree with, and nuke any nodes critical of E2 editorial policy itself. In one case, they outright banned a user who had extreme right wing opinions nobody liked very much. Of course, the guy who writes thestileproject.com got banned in seconds flat. There is no appeal, and if a node gets nuked there's no way for the writer to retrieve that content.

27. So, should you fire your IA’s and let your users structure your content?

28. Yes!

29. I mean, No! • Obviously, there must be an initial organization • Create an organization that is flexible, not rigid • But make sure what changes are the connections, not the addresses

30. Those %$&$#! Three Circles BusinessContext Content Users

31. Further Concerns • Data analysis – sooper-dooper important • Make sure your project has a real mission • Close watch—site structures based on use require a community… And online communities require gardeners to nurture them

32. A Quick and Dirty Algorithm • http://pespmc1.vub.ac.be/INFOJB.html • Frequency—reinforce a link (AB) that a person traverses • Symmetry – reinforce reverse link (BA), a little less • Transivity – If a person goes AB and BC, reinforce AC • This is what leads to true restructuring

33. Future Uses

34. Peer to peer • Think beyond music • Think of an ever-shifting stream of information • “Architect” that

35. Personal Categorization • If I’m involved in SO/HO, I’m not interested in ‘electronics’ or ‘computers,’ ’I’m interested in what can help me

36. Evolutionary Model • Again and again it’s been shown that attempts at God-like ‘organized’ top-down design typically fail • Too many contingencies, too chaotic • Bottom-up, rules-based structures adopt, adapt, and improve • Organization without explicit design is very powerful

37. From http://pespmc1.vub.ac.be/papers/namurart.html • “We believe the laws of evolution, in which natural selection guarantees the survival of the fit and the extinction of the unfit, apply in all cases whether living beings, dead matter or knowledge is concerned. Ideas, chunks of knowledge, can be considered specific entities that rely on human or other carriers to multiply, mutate, adapt and survive. The human population and the technology devoted to communication can likewise be regarded as a huge ecology populated by ideas, theories or knowledge in general. The Internet has in the most recent years been becoming an integral part of this so-called ecology of knowledge…”

38. Sites need to evolve structures • Evolution requires • An Environment • In which elements are • Selected • Based on their • Fitness • --Natural Selection

39. Natural selection • White and black moths

40. Sites need to evolve structures • Structures require • Principles • In which • Meaningful organization • Arises from a • Significantly complex system • --Self organization

41. Self organization • Astronomical phenomena, crystal structures

42. Resources • Principia Cybernetica Web - http://pespmc1.vub.ac.be/SUPORGLI.html • Self-Organizing Systems FAQ - http://www.calresco.org/sos/sosfaq.htm • The Symbiotic Intelligence Project - http://ishi.lanl.gov/symintel.html • Cosma Shalizi’s Notebooks on Self-Organization - http://www.santafe.edu/~shalizi/notebooks/self-organization.html • Social Computing Program - http://www.sics.se/humle/socialcomputing/ • ReferralWeb - http://www.cs.washington.edu/homes/kautz/referralweb/index.html • The Origins of Order and At Home in the Universe, Stuart Kauffman • Women, Fire, and Dangerous Things, George Lakoff • How Buildings Learn, Stewart Brand