Applying Web 2.0 Design
Principles in the
Design of Cooperative
Applications
Niels Pinkwart
Clausthal University of Technology
[email protected]
Talk Outline
 Part 1: Social Software systems vs. traditional
Groupware - Five dimensions of comparison
 Part 2: The LARGO System - Social Software for legal
argumentation
 Conclusion
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Social Software vs. Groupware
Groupware
Social Software
 Software products of CSCW
 Exists since 1980’s
 Designed to support intentional group
 Not a result of CSCW research
 Term coined in 2002
 All kinds of systems that support
processes
 Serve users with shared aims or goals
 Enable users to collaborate via shared
group interaction even when that
interaction is offline
media
 Do often not gain much attention in
practice
 Highly successful, millions of users,
media attention
Similar aims and definitions – where are differences?
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Criterion 1: Application Areas
Groupware
Social Software
 Traditionally oriented towards
 Much greater variety of
supporting group work and
enabling collaborators to interact
efficiently and effectively
 Note: CSCW 2008 sessions will
include Wikis & Wikipedia,
Naughty & Nice issues in Social
Networking Systems, Gaming,
Health Informatics, and
Deployments at Home
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application areas, including areas
such as hobbies, leisure, or play
 tools are less driven by goals
like productivity and efficiency
 Work related Social Software
exists prominently – e.g., XING,
linkedin
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Criterion 2: Control
Groupware
Social Software
 System side control about possible
 Typically very open: they delegate a
user actions is an important factor:
groupware tools are often about
scaffolding a group collaboration
process – this implies a certain
intervention in the options of single
users in order to coordinate the
overall group workflow.
 User rights often determined based on
role and hierarchy in company
 Process control is important factor
(e.g., BPMN, IMS-LD)
lot of control to the users and the
user community. E.g., Wikipedia
entries not centrally reviewed/edited
by default. Quality control by social
protocols and technology support
 Trust often achieved through
reputation system (e.g., Ebay)
 No central authority that assigns the
status based on company organization
or some other hierarchy
 Little “process control”: Where
predefined processes exist at all,
these are usually simple
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Criterion 3: Technology Requirements
Groupware
Social Software
 Groupware tools are often
 Typically rather “low tech” client-
research products, used to study
how state-of-art technologies can
be used to support group
interactions (e.g., big wall
displays, high-end cell phones, …)
 Their use thus requires buying (or
already owning) the specific
hardware
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side and requires not more than
Web access and a simple piece of
software, often only a browser
 JavaScript and XML (e.g., AJAX,
DHTML) technical base for
successful systems like last.fm,
amazon, Ebay
 Avoidance of expensive
proprietary technology enables
masses of users to use the
system
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Criterion 4: Success Factors
Groupware
Social Software
 Frequently tailored towards smaller
 Participation is key success factor for
but more structured groups and group
processes - systems like shared
calendars, collaborative text editors,
meeting room technologies or shared
workspace systems do not need huge
user communities
 Quality and practical value are largely
determined by productivity or
functionality gains for group
 Measurement of system success is a
research question – typically
interdisciplinary (socio-technical
systems)
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Social Software, since these systems
live from the interactions of their
(large) user communities
 Therefore: extremely easy to use and
do not require complicated software
installations and configurations
 Benefits of the systems are clearly
visible for the users and often also
available for non-members (e.g., flickr,
Wikipedia, amazon)
 Usability and immediate benefit
motivate the system usage - a Social
Software tool without a large user
base would not be called successful
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Criterion 5: Algorithms
Groupware
Social Software
 CSCW research involves wide variety
 The one by far most prominent and
of algorithms – e.g., methods for
controlling concurrent text editing,
algorithms for calculating and
displaying awareness information, etc.
widely used type of algorithm is
collaborative filtering
 Through their actions in the system
(buying or looking at books at
amazon.com, entering profiles in
online dating services or tagging
images on flickr), users get associated
to system artifacts in various ways
 System exploits this to recommend
artifacts to other users
 Analyzing user actions to generate the
added value of the system is
algorithmic core of Social Software –
here, collaborative recommendations
play key role
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Social Software vs. Groupware
 Summary result 1: Groupware tools and Social Software applications are
not the same – they do have differences
 Most prominent common point is aim: facilitating group interactions and
communications
 Most important differences: technology requirements, degrees of user
control and application areas
 Summary result 2: These differences are neither strictly defined through
clear-cut rules nor overwhelming or a necessity
 Summary result 3: Fields tend to merge - CSCW researchers can learn
from Social Software success factors to improve the level of collaboration
and the practical impact of the systems they design
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Example: An ITS for legal argumentation




LARGO (Legal ARgument Graph Observer)
System design approach: Engage student groups in analyzing,
visualizing & reflecting about examples of expert Socratic
reasoning
Not driven primarily by the idea of developing “Social Software”

To the contrary, LARGO is designed for rather small groups where
users have to work through a well-specified task without having a
great degree of control

Also: the success of the system is finally subject to empirical
studies of learning and not a question of widespread usage
But: Application of social software principles


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Markup, “tagging” resources, recommending objects created by
peers
Collaborative filtering employed as tool to generate better
feedback in Intelligent Tutoring System
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US Supreme Court Oral Arguments

Important part of decision process

Attorneys propose a decision rule (“test”) to determine how to
decide a case

Justices challenge these tests, often by posing hypothetical
scenarios

Educationally valuable (but difficult) material for students
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An Example Case

Example: Lynch v. Donnelly 465 U.S. 668 (1984)

Facts: The city of Pawtucket annually erected a Christmas
display located in the city's shopping district. The display
included such objects as a Santa Claus house, a Christmas tree,
a banner reading "Seasons Greetings," and a nativity scene.

Question: Did this violate the constitutional separation of
Church and State?
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Example: Tests and Hypotheticals
MR. DE LUCA: With the possible exception of the cross, the nativity scene is one of
the most powerful religious symbols in this country, and most certainly one of the
most powerful Christian religious symbols in this country. (…) Pawtucket's
Test
purchase, the maintenance, and the erection of the fundamental Christian symbol
involves government in religion to a profound and substantial degree. (…)
JUSTICE: Now, if the city did not own the crèche itself, so that everything that was
contributed to the display, including the crèche, were privately owned, it wouldn't
violate the First Amendment, the fact that it was right next door to the City Hall,
Hypo
would it?
MR. DE LUCA: I think that in understanding that the city owns all of the symbols and
all of the artifacts that are contained in this display, and assuming that the crèche
were purchased and paid for privately without any other explanation that it is
private, then I think it would still violate the establishment clause for the First
Amendment, because there is no indication to anyone looking at that that the
display or the crèche is not part of the broader display which is put up and
Test
Modif.
sponsored by the city. (…)
JUSTICE: Would you regard the prayer that I spoke of to your friend in the House or
the Senate or in any state legislature as purely symbolic, or is it a matter of
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Applying Web 2.0 Design Principles in the Design of Cooperative Applications
substance?
Hypo
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An Example LARGO Diagram
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Intelligent Support



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How help students

analyze the argument transcript?

navigate the interlinked information spaces?
Automated diagram analysis allow for:

Graph structure inspection
 general argumentation principles, e.g. “there should be at
least one test”

Checks of links between graph and transcript
 case specific “important passages”
Not subject of this talk
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Content Analysis?
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Feedback in LARGO
Idea:
 Make use of peer students working on the same task
 Have students rate peer solutions as part of their working with the
system
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Feedback in LARGO

Exploit that the system knows
what part of the graph refers to
certain important parts of text…
Student A
Student C
Student B
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Feedback in LARGO

… and use these relations to
generate the dialogs
Student A
Student C
Student B
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Collaborative Filtering in LARGO
Principle for quality rating q: weighted average of base rating and
evaluation rating (0=poor, 1=excellent)

Base rating
 Based on how student rates other solutions
 Serves as initial score heuristic, immediately available
 Assumption: having good solution correlates to recognizing
good solutions
n
1 k

b    qi   (1  qi ) 
n  i 1
i  k 1

Recommended items
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Non-recommended items
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Collaborative Filtering in LARGO

Evaluation rating
 Based on recommendations a student’s answer receives (or
not), and by whom
 Develops over time
 Takes peer opinions into account
 Assumption: measures actual quality
p
e
q
i
Actual recommenders
q
i
All possible recommenders
i 1
j
i 1
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Conclusion
 Social Software and traditional Groupware
 Both terms used for systems that facilitate social interaction
 Clear borderline cannot be drawn
 Differences exist in terms of application areas, degrees of user control,
technology requirements, success factors and algorithms
 But: differences are not necessity – success factors of Social Software
can be used to inform the system design of CSCW systems
 Example: The LARGO system
 Groupware for legal argumentation training
 Cooperative visualization of arguments
 Makes use of Social Software design paradigm “collaborative filtering”
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