2007 kmworld presentation on augmented social cognition research at parc

Web 2.0 in the Enterprise Improving collaboration through research insights in coordination costs

KMWorld & Intranets 2007 November 7, 2007

Ed H. Chi, Ph.D. Manager, Augmented Social Cognition Area [email protected]

Lawrence C. Lee Director of Business Development [email protected]

Intelligent Systems Laboratory Palo Alto Research Center Inc.

2 KM World & Intranets 2007 – © 2007 Palo Alto Research Center Inc.

PARC Overview

  Interdisciplinary research center

  Founded in 1970

  Spun out of Xerox in 2002

  Business model: –  Contract research –  Licensing

–  Joint ventures

–  Spinoffs


Web 2.0 and Enterprise 2.0

Software as a Service (SaaS)

Rich User Interactions

Network Effects and Collective Intelligence

Remixing and Mashup of Services

Disruptive Potential

Social Networks

New Collaboration Environments


Benefits of Web 2.0

  Web 2.0 tools in the enterprise: –  Blogs –  Wikis –  Social bookmarking –  RSS –  Search –  Social networking

  Benefits –  Simple to set up –  Easy to use –  Knowledge captured as side effect of communication


Costs of Web 2.0

  Benefits of Web 2.0 do not come for free –  Interference effects –  Interaction costs –  Noisy folksonomies

  Research Methodology –  Analyze activity on social systems –  Develop models on interaction dynamics –  Design new systems to increase benefits and reduce cost –  Test systems in Living Laboratories


Research Foundation

  PARC’s rich history of research in information systems –  User interface research –  Information foraging theory –  Sensemaking

  Augmented Social Cognition –  Vision: Enhance the ability of a group of people to remember,

think, and reason –  Combines cognitive science with social computing research


Outline

  Overview –  Benefits of Web 2.0 in the Enterprise

–  Costs of Web 2.0 »  Interference effects, interaction costs, noisy folksonomies

  Three examples of PARC research and solutions –  WikiDashboard: Providing social transparency in Wikispaces

–  SparTag.us: Lowering interaction costs in tagging systems

–  TagSearch: Reducing noise in tagged data and harnessing tags for search


I. Interference Effects in Wikipedia

Source: Wikipedia (Kittur, Suh, Pendelton, Chi)

Declining percentage of activity devoted to article editing in Wikipedia


Mediators

Sympathetic to parents

Sympathetic to husband

Anonymous (vandals/spammers)

Revert Graph for Wikipedia page: Terry Schiavo

Visualizing Interference and Conflict

Source: Wikipedia (Kittur, Suh, Pendelton, Chi)


WikiDashboard

  Transparency of social dynamics can reduce conflict and coordination issues –  WikiDashboard: Social dashboard for wikis –  Prototype system: http://wikidashboard.parc.com

  Visualization for every wiki page showing edit history timeline and top individual editors

  Can drill down into activity history for specific editors and view edits to see changes side-by-side


WikiDashboard Summary

  Key problems –  Lack of visibility into social dynamics of wikis –  Lack of transparency in individual activity

  PARC’s solution –  Visualization of individual edit activity to increase

transparency, accountability, and quality of wikis –  Connect individuals with shared interests by reviewing

activity on specific wiki topics


II. Interaction Costs and Social Systems

  Interaction costs determine number of people who participate

  Surplus of attention & motivation at small transaction costs

  Therefore…   Important to keep

interaction costs low Cost of participation

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Social Bookmarking

  Means of storing, annotating, and sharing links

  Typically done for oneself   But implicit sharing promotes

transfer of expertise   Lightweight form of enterprise

knowledge sharing   Players:

–  Del.icio.us –  Connotea –  CiteUlike –  and many enterprise social

bookmarking systems (that operate behind the firewall)


SparTag.us

  Social bookmarking is easy to do but there is still friction in the process –  Tagging in new window separate from document –  Tagging limited to page level even though you want to tag a

paragraph only –  Tags and annotations do not remain with paragraphs if

referenced on other pages

  New approach: Make tagging and retrieval of tagged content easier

  Lower interaction costs and increase participation


SparTag.us

  Key innovations –  Click-to-tag –  Paragraph-level tags –  Social annotations –  Tag portability

Highlights (annotations)

Paragraph-level tagging


My SparTag.us

  Web-based notebook keeps track of all clipped paragraphs with tags and highlights


SparTag.us Summary

  Key problems –  Friction in current tagging process –  Tags are limited to page level only –  Difficult to find content of interest on page later

  PARC’s solution –  In situ tagging on the same page using click-to-tag –  Tags applied to paragraphs –  Tags and annotations stay with paragraph, even on new

pages (e.g. block quote on a blog post) –  My SparTag.us notebook displays all tagged and annotated

paragraphs


III. Noise in Social Tagging Systems

  Folksonomies emerge from social tagging systems

  Benefits –  Freeform tagging instead of conforming to rigid taxonomies –  More flexibility allows users to recall information later –  Information discovery using tag browsing

  Weaknesses –  Noise –  Inconsistency –  Difficult to leverage for search


Think of tagging as a communication… Topics Concepts

Users Documents Tags T1…Tn Encoding Decoding

Noise


Information Theoretic Measures

  Mutual information I(Doc; Tag) –  Amount of information

known about documents given knowledge of tags

  Conditional entropy H(Doc|Tag) –  Additional amount of

information needed to be known in order to identify a document given knowledge of tags

Knowledge of tags

Knowledge of documents

I(Doc;Tag) H(Doc|Tag)


I(Doc; Tag)

  Tags contain less information about documents over time

Source: del.icio.us (Chi & Mytkowicz)


H(Doc | Tag)

  More information needs to be known over time, over and above what is given by tags



Rise in Average Tags per Bookmark

  Note parallel with increasing average number of words in a search query



•  Synonyms •  Misspellings •  Morphologies

People use different tag words to express similar concepts.

But Social Tagging Creates Noise


Guide

Web

Howto

Tips Help

Tools

Tip

Tricks

Tutorial

Tutorials

Reference

Semantic Similarity Graph

Use Semantic Analysis to Reduce Noise


TagSearch – A New Search Engine

  New approach: harness human intelligence encoded in tags on documents and web pages to improve search precision


TagSearch Summary

  Key problems –  Noisy tag data –  Users do not want to conform to rigid taxonomies –  Too many irrelevant results in enterprise search

  PARC’s solution –  Let users tag freeform but use data mining techniques to

reduce noise –  Harness normalized tag data in new search algorithm –  Result: High precision enterprise search engine trained on

content tagged by enterprise community


Conclusion

  Effective deployment of Web 2.0 tools requires understanding of both costs and benefits. –  Increasing transparency results in higher quality –  Lowering interaction costs results in higher participation –  Decreasing noise results in greater search precision

  PARC works with enterprises to solve specific problems and deploy customized versions of its suite of Web 2.0 technologies.


Contacts

  Stop by our booth at the Expo - Booth 313   Our contact information:

Ed H. Chi, Ph.D. Manager, Augmented Social Cognition Area [email protected] 650.812.4312

Lawrence C. Lee Director of Business Development [email protected] 650.812.4756

2007 kmworld presentation on augmented social cognition research at parc

Business

research insights

firewallkm world intranets

social transparency

examples of parc research

social dashboard

enterprise costs of

social cognition area

social cognition vision