Enhancing the Social Web through Augmented Social Cognition Research

2,263 views

Published on

Keynote talk given at the International Conference on Asia-Pacific Digital Libraries (ICADL) 2008. December, 2008 in Bali, Indonesia ICADL 2008 link here

We are experiencing the new Social Web, where people share, communicate, commiserate, and conflict with each other. As evidenced by Wikipedia and del.icio.us, Web 2.0 environments are turning people into social information foragers and sharers. Users interact to resolve conflicts and jointly make sense of topic areas from "Obama vs. Clinton" to "Islam."

PARC's Augmented Social Cognition researchers -- who come from cognitive psychology, computer science, HCI, sociology, and other disciplines -- focus on understanding how to "enhance a group of people's ability to remember, think, and reason". Through Web 2.0 systems like social tagging, blogs, Wikis, and more, we can finally study, in detail, these types of enhancements on a very large scale.

In this talk, we summarize recent PARC work and early findings on: (1) how conflict and coordination have played out in Wikipedia, and how social transparency might affect reader trust; (2) how decreasing interaction costs might change participation in social tagging systems; and (3) how computation can help organize user-generated content and metadata.

Published in: Technology, Education

Enhancing the Social Web through Augmented Social Cognition Research

  1. 1. Enhancing
the
Social
Web
through
Augmented Social
Cognition
research Ed
H.
Chi Peter
Pirolli,
Lichan
Hong,
Bongwon
Suh,
Gregorio
Convertino, Les
Nelson,
Rowan
Nairn Augmented
Social
Cognition
Area Palo
Alto
Research
Center Interns:
Terrell
Russell,
Brynn
Evans,
Bryan
Chan,
KMRC
students Alumni:
Raluca
Budiu,
Bryan
Pendleton,
Niki
Kittur,
Todd
Mytkowicz 2008-11-07 Ed H. Chi ASC Overview 1 Image from: http://www.flickr.com/photos/ourcommon/480538715/
  2. 2. FOUNDING
VISION
FOR
PARC  Bold
strategic
investment – Founded
bysemiconductors,
software,
systems – 
Xerox
in
1970,
recognition
of
the
coming
digital
revolution – Chartered
the
organization
to
create
“The
Office
of
the
Future” – Challenged
researchers
to
become
the
“architects
of
information”  Unique
multi‐disciplinary
culture – Physicists,
electronics
engineers,
computer
scientists…theory
&
practice – Able
to
see
problems
and
integrate
solutions
from
multiple
perspectives 2008-11-07 Ed H. Chi ASC Overview 2
  3. 3. 14 years of work in foraging and sensemaking  Information
Scent – WUFIS
/
IUNIS
(Basic
scent
modeling
algorithms) [CHI2000,2001] – Bloodhound
(Simulation
of
web
navigation)
[CHI2003] – LumberJack
(Log
analysis
of
user
needs)
[CHI2002]  Information
Foraging – ScentTrails
[TOCHI2003] – ScentIndex
[CHI2004] – ScentHighlight
[IUI2005] – Visual
foraging
of
highlighted
text
[HCII]  Sensemaking – Visualization
of
Web
Ecologies
[CHI98] – Visualization
Spreadsheets
[Infovis97,
Infovis99] 2008-11-07 Ed H. Chi ASC Overview 3
  4. 4. What
is
Web2.0? What
is
Augmented
Social
Cognition? And
how
are
they
related? 2008-11-07 Ed H. Chi ASC Overview 4
  5. 5. What
is
Wikipedia? “Wikipedia is the best thing ever. Anyone in the world can write anything they want about any subject, so you know you’re getting the best possible information.” – Steve Carell, The Office 2008-11-07 Ed H. Chi ASC Overview 5
  6. 6. Wikipedia 2008-11-07 Ed H. Chi ASC Overview 6
  7. 7. High‐end
of
the
collaboration
spectrum  Groups
utilize
systems
to make
sense
and
share complex
topics
and materials.  Wikipedia
(social
status)  Slashdot
(karma
points)  WikiHow.com  Lostpedia.com 2008-11-07 Ed H. Chi ASC Overview 7
  8. 8. Middle
of
the
spectrum  Systems
that
evolve
structures that
can
be
used
to
organize information.  Del.icio.us  Flickr  YouTube  Friendster 2008-11-07 Ed H. Chi ASC Overview 8
  9. 9. Lightweight
social
processes  Counting
votes – A
way
to
increase
signal‐to‐noise
ratio – Information
faddishness  Examples: – Digg.com – Most
bookmarked
items
on
del.icio.us – Estimating
the
weight
of
an
ox
or temperature
of
a
room – The
true
value
of
a
stock – PageRank
or
Hub
/
Authority
algorithms 2008-11-07 Ed H. Chi ASC Overview 9
  10. 10. A
way
to
think
about
these
systems Voting systems Col. Information Collaborative Structures Co-Creation Digg.com eHow.com IBM dogear Wikipedia PageRank Del.icio.us Flickr Slashdot Naver Heavier collaboration 2008-11-07 Ed H. Chi ASC Overview 10
  11. 11. Layers
of
Models
Needed Voting systems Col. Information Collaborative Structures Co-Creation Digg.com Understanding of eHow.com Understanding of info Understanding of micro-economics and social networks IBM dogear Wikipedia conflicts and PageRank coordination • of foraging [PARC] Del.icio.us Flickr • Tag network analysis [PARC, Slashdot Naver Golder, Yahoo] • Wikipedia coordination • Personal vs. group costs [PARC] [Huberman, Adamic] • Structural holes (info brokerage) Heavier • Invisible Colleges [Sandstrom] • Wisdom of Crowd [Burt] collaboration effects [Pirolli] • Interference [Surowieki] • Network constraints and • Co-laboratories [Olson and • Information cascades structure [various] Olson] • Community networks / Col. [Anderson and Holt] • Semantic of semiotic structures / Problem solving [Carroll] words [IR, LSA] 2008-11-07 Ed H. Chi ASC Overview 11
  12. 12. Research
Vision Augmented
Social
Cognition  Cognition:
the
ability
to
remember,
think,
and
reason;
the
faculty
of knowing.  Social
Cognition:
the
ability
of
a
group
to
remember,
think,
and reason;
the
construction
of
knowledge
structures
by
a
group. – (not
quite
the
same
as
in
the
branch
of
psychology
that
studies
the cognitive
processes
involved
in
social
interaction,
though
included)  Augmented
Social
Cognition:
Supported
by
systems,
the enhancement

of
the
ability
of
a
group
to
remember,
think,
and reason;
the
system‐supported
construction
of
knowledge structures
by
a
group. Citation:
Chi,
IEEE
Computer,
Sept
2008 2008-11-07 Ed H. Chi ASC Overview 12
  13. 13. Understanding
a
new
area… Characteriza*on Models Evalua*ons Prototypes 2008-11-07 Ed H. Chi ASC Overview 13
  14. 14. Characteriza*on Models Evalua*ons Prototypes 2008-11-07 Ed H. Chi ASC Overview 14
  15. 15. Conflict/Coordination
Effects
in
Wikipedia [Kittur
et
al.,
CHI2007] 100% 95% Maintenance 90% Percentage of total edits Other 85% 80% User Talk 75% User 70% Article Talk 65% Article 60% 2001 2002 2003 2004 2005 2006 (joint work with Niki Kittur, Bongwon Suh, Bryan Pendleton) 2008-11-07 Ed H. Chi ASC Overview 15
  16. 16. Conflict
in
Wikipedia  Conflict
is
growing
at
the
global
level,
and
we
have some
idea
about
where
it
is.  But
what
defines
conflict
inside
Wikipedia?  Build
a
characterization
model
of
article
conflict – Identify
metrics
relevant
to
conflict – Automatically
identify
high‐conflict
articles 2008-11-07 Ed H. Chi ASC Overview 16
  17. 17. Measure
of
controversy  “Controversial”
tag  Use
#
revisions
tagged
controversial 2008-11-07 Ed H. Chi ASC Overview 17
  18. 18. Page
metrics  Possible
metrics
for
identifying
conflict
in
articles Metric type Page Type Revisions (#) Article, talk, article/talk Page length Article, talk, article/talk Unique editors Article, talk, article/talk Unique editors / revisions Article, talk Links from other articles Article, talk Links to other articles Article, talk Anonymous edits (#, %) Article, talk Administrator edits (#, %) Article, talk Minor edits (#, %) Article, talk Reverts (#, by unique Article editors) 2008-11-07 Ed H. Chi ASC Overview 18
  19. 19. Performance:
Cross‐validation  5x
cross‐validation,
R2
=
0.897 10000 9000 Actual controversial revisions 8000 7000 6000 5000 4000 3000 2000 1000 0 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 2008-11-07 Predicted controversial revisions Ed H. Chi ASC Overview 19
  20. 20. Performance:
Cross‐validation  5x
cross‐validation,
R2
=
0.897 10000 9000 Actual controversial revisions 8000 7000 6000 5000 4000 3000 2000 1000 0 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 Predicted controversial revisions 2008-11-07 Ed H. Chi ASC Overview 20
  21. 21. Determinants
of
conflict  Highly weighted features of conflict model:  Revisions
(talk)  Minor
edits
(talk)  Unique
editors
(talk)  Revisions
(article)  Unique
editors
(article)  Anonymous
edits
(talk)  Anonymous
edits
(article) 2008-11-07 Ed H. Chi ASC Overview 21
  22. 22. Surplus
of
Attention


[Shirky] source: xkcd 2008-11-07 Ed H. Chi ASC Overview 22
  23. 23. Revert
Graph
[Suh
et
al.,
IEEE
VAST
2007]  Research
Goal – How
can
we
identify
point
of
views
between
users? – Group
people
share
a
common
point
of
view  Using
revert
as
proxy
for
disagreement
between
users – Revert
edits:





3,711,638 6.3
%
of
total
edits – Due
to
vandalism:
577,643 0.99%
of
total
edits
(15.6%
of
reverts)  Force
directed
layout – Node:
user,
Edge:
revert
relationship 2008-11-07 Ed H. Chi ASC Overview 23
  24. 24. Opinions
on
Dokdo/Takeshima Group D Group A Group B Group C Number of users in user group A B C Total Users with Korean point of view 10 6 0 16 Users with Japanese point of view 1 8 7 16 2008-11-07 Neutral ASC Overview Ed H. Chi or Unidentified 7 3 6 2417
  25. 25. Mediator
Pattern
‐
Terri
Schiavo Anonymous (vandals/spammers) Sympathetic to husband Mediators Sympathetic to parents 2008-11-07 Ed H. Chi ASC Overview 25
  26. 26. Using
Information
Theory
to
Model
Social
Tagging [Ed
H.
Chi,
Todd
Mytkowicz,
ACM
Hypertext
2008] [Ed
H.
Chi,
Todd
Mytkowicz,
ACM
Hypertext
2008] Concepts Topics Users Documents Noise Tags Decoding Encoding T1…Tn 2008-11-07 Ed H. Chi ASC Overview 26
  27. 27. H(Tag)
shows
saturation
in
tag
usage 2008-11-07 Ed H. Chi ASC Overview 27
  28. 28. H(Doc
|
Tag),
browsability 2008-11-07 Ed H. Chi ASC Overview 28
  29. 29. Raise
in
avg.
tag
per
bookmark (note
parallel
the
development
in
increasing
#
of
query
words) 2008-11-07 Ed H. Chi ASC Overview 29
  30. 30. I(Doc;
Tag)

Mutual
Information Source: Hypertext 2008 study on del.icio.us (Chi & Mytkowicz) 2008-11-07 Ed H. Chi ASC Overview 30
  31. 31. Understanding
a
new
area… Characteriza*on Models Evalua*ons Prototypes 2008-11-07 Ed H. Chi ASC Overview 31
  32. 32. Living
Laboratory: Prototyping
Social
Applications
on
the Internet Create
a
Living
Laboratory
as
a
platform
to develop,
test,
and
market
innovations 2008-11-07 Ed H. Chi ASC Overview 32
  33. 33. WikiDashboard: Social
Transparency
for
Wikipedia Joint
work
with Bongwon
Suh,
Aniket
Kittur,
Bryan
Pendleton Bongwon
Suh,
Ed
H.
Chi,
Aniket
Kittur,
Bryan
A.
Pendleton.
Lifting
the Veil:
Improving
Accountability
and
Social
Transparency
in
Wikipedia
with WikiDashboard.
In
Proceedings
of
the
ACM
Conference
on
Human‐factors in
Computing
Systems
(CHI2008).
ACM
Press,
2008.
Florence,
Italy. 2008-11-07 Ed H. Chi ASC Overview 33
  34. 34. Risks
in
Using
Wikipedia
[Denning
et
al.
2005]  Factual
accuracy  Motives
of
editors  Uncertain
expertise  Volatility  Spotty
coverage  Unproven/non‐independent
source 2008-11-07 Ed H. Chi ASC Overview 34
  35. 35. Social
Dashboard  Social
translucent
for
effective
communication
and
collaboration [Erickson
and
Kellogg
2002] – Make
socially
significant
information
visible
and
salient – Support
awareness
of
the
rules
and
constraints – Accountability
for
actions  Wikis
can
be
a
prime
candidate – Every
edit
is
logged
and
retrievable – WikiScanner.com:
analyze
anonymous
IP
edits – WikiRage.com:
top
edits 2008-11-07 Ed H. Chi ASC Overview 35
  36. 36. Hillary
Clinton 2008-11-07 Ed H. Chi ASC Overview 36
  37. 37. Top
Editor
‐
Wasted
Time
R 2008-11-07 Ed H. Chi ASC Overview 37
  38. 38. Subprime
Mortgage
Crisis 2008-11-07 Ed H. Chi ASC Overview 38
  39. 39. WikiDashboard  Surfacing
hidden
social
context
to
users  For
readers – Any
incidents
in
the
past
e.g.
A
sudden
burst
of
edits? – Who
are
the
top
editors? – What
is
their
motivation
/
point
of
views
/
expertise
/
topics
of interest? – Help
them
judging
the
quality/trustworthiness/usefulness
of
an article.  For
writers – Measure
expertise
/
contribution
/
reputation – Motivate
them
to
be
more
active
/
responsible
(?) 2008-11-07 Ed H. Chi ASC Overview 39
  40. 40. MrTaggy.com: social
search
with
tags Joint
work
with Rowan
Nairn,
Lawrence
Lee,
Peter
Lai,
Lichan
Hong 2008-11-07 Ed H. Chi ASC Overview 40
  41. 41. TagSearch




http://mrtaggy.com http://mrtaggy.com Semantic Similarity Graph Web Tools Reference Guide Howto Tutorial Tips Help Tip Tutorials Tricks 2008-11-07 Ed H. Chi ASC Overview 41
  42. 42. SparTag.us: Social
Paragraph‐level
Tagging Joint
work
with Lichan
Hong,
Raluca
Budiu,
Les
Nelson,
Peter
Pirolli Lichan
Hong,
Ed
H.
Chi,
Raluca
Budiu,
Peter
Pirolli,
and
Les
Nelson.
SparTag.us:
A
Low Cost
Tagging
System
for
Foraging
of
Web
Content.
In
Proceedings
of
the
Advanced Visual
Interface
(AVI2008),
(to
appear).
ACM
Press,
2008. 2008-11-07 Ed H. Chi ASC Overview 42
  43. 43. Lowering
Participation
/
Interaction Costs  Interaction
costs # People willing to produce for “free” determine
number
of people
who
participate  Surplus
of
attention
& motivation
at
small transaction
costs  Therefore…  Important
to
keep interaction
costs
low Cost of participation 2008-11-07 Ed H. Chi ASC Overview 43
  44. 44. SparTag.us  In situ tagging while reading – No new window – Clicking vs typing  Tagging + highlighting 2008-11-07 Ed H. Chi ASC Overview 44
  45. 45. Paragraph
Tagging  Intuition:
sub‐doc
nuggets
useful – Entities,
facts,
concepts,
paragraphs  Annotations
attached
to

paragraphs  Portable
across
pages
and
other
contents
(e.g. Word
documents) – Dynamic
pages – Duplicate
content 2008-11-07 Ed H. Chi ASC Overview 45
  46. 46. Example:

Duplicate

Content 2008-11-07 Ed H. Chi ASC Overview 46
  47. 47. My

Reading
Notebook 2008-11-07 Ed H. Chi ASC Overview 47
  48. 48. Social

Sharing friend’s highlights my highlights my tags friend’s tags 2008-11-07 Ed H. Chi ASC Overview 48
  49. 49. Importance

Indicator recall first-visit 2008-11-07 Ed H. Chi ASC Overview 49
  50. 50. Two

Sides
of
Tagging Encoding Retrieval “video

people

talks
technology”
 h>p://www.ted.com/index.php/speakers h>p://edge.org “science

research
cogni*on” 50 2008-11-07 Ed H. Chi ASC Overview 50
  51. 51. Augmented
Social
Cognition
questions:  Crowdsourcing
[collaborative
co‐creation] – Is
there
a
wisdom
of
the
crowd
in
Wikipedia? – How
does
conflict
drive
content
creation?  Collective
Intelligence
[folksonomy] – Are
social
tags
collectively
gathered
useful
for
organization
of
a
large document
collection?  Collective
Averaging
[social
attention] – Does
voting
systems
identify
the
best
quality
and
most
interesting information
for
that
community?  Participation
Architecture
[interaction] – Does
lowering
the
interaction
cost
barrier
increase
participation productively?  Expertise
finding
[social
networking] – Does
getting
experts
through
social
network
gets
you
to
better
quality information
sooner? 2008-11-07 Ed H. Chi ASC Overview 51
  52. 52. The
Team 2008-11-07 Ed H. Chi ASC Overview 52
  53. 53. Augmented
Social
Cognition: From
Social
Foraging
to
Social
Sensemaking  Research
Vision:
Understand
how
social
computing systems
can
enhance
the
ability
of
a
group
of people
to
remember,
think,
and
reason.  Living
Laboratory:
Create
applications
that
harness collective
intelligence
to
improve
knowledge capture,
transfer,
and
discovery. http://asc‐parc.blogspot.com http://www.edchi.net echi@parc.com 2008-11-07 Ed H. Chi ASC Overview 53 Image from: http://www.flickr.com/photos/ourcommon/480538715/

×