Exploring Human Computation and Social Computing to Inform
the Design Process
Roberto Romani
and Maria Cecília Calani Baranauskas
Institute of Computing, Unicamp, Av. Albert Einstein, 1251 Campinas, SP, Brazil
Keywords: GWAP, HCI, GWIDO, Social Network, Human-Centered Computing, Culture of Participation.
Abstract: Although several standards, recommendations and guidelines have been used to assist designers in their
tasks, much of the design choices still rely heavily on the designer’s experience. In this work we argue that
complex choices about interface elements (e.g. images, icons, sounds) could have the help of the users
themselves to inform the designer´s choices. The paper situates the contribution in the intersection of the
human computation and social computing fields, showing a preliminary survey of related work. Moreover,
we illustrate the idea with an instantiation of an environment for designers, within the frontiers of human
computation and social computing.
1 INTRODUCTION
Since the HCI beginning, designers of interactive
applications have been using several techniques to
understand the users' tasks, their needs and potential
new features that might improve the users’ activities.
Although these techniques are constantly being
improved, the challenge has increased especially
because of the development of new electronic
mobile devices, the web evolution and consequent
diversity of users.
When the scope of an application is well-defined
and the set of potential users is limited and
homogenous, designers may use traditional HCI
techniques to work the user interface elements
representations in tune with the users’ profile.
However, the interaction design becomes more
difficult as the number of user classes and systems
requirements increase. In this context new support to
the design process must be provided to capture this
diversity.
The design for all (University N.C.S, 2008)
approach proposes that systems should be projected
for a huge variety of users with different conditions
and needs. According to the HCI practice, the user is
the most indicated stakeholder to validate the
interfaces projected by designers, as well as to
contribute during the design process. In several
design projects it is difficult to involve a large and
varied number of users through conventional user
centered or participatory design methods. Thus,
designers solve such difficulties adapting techniques
and using their own experience. However, the web
provides resources which can be used as an efficient
mechanism of “unlimited” access to different users’
classes worldwide.
This idea of using applications and services that
facilitate collective action and online social
interaction is associated to the term “social
computing”. Several technologies such as blogs,
wikis and online communities are examples of social
computing. Although the scope of the term is broad,
it includes humans in a social role where technology
mediates the human communication. Thus, these
aspects of the web could be used to provide a virtual
space for designers to share experiences in order to
propose design elements more suitable to users.
Although several standards, recommendations
and guidelines are used to assist in the user
interfaces development, much of the design still
relies heavily on the designer’s experience and
knowledge. In other words, important decisions on
specific parts of interface design such as choices
about images, icons, sounds and other interface
elements are complex tasks that could have the help
of humans themselves to inform the designer´s
choices. For example, for a computer system,
defining the best image among many to represent a
concept such as “schedule meeting”, is unthinkable.
However, users can quickly choose which image is
most representative for the concept. The paradigm
that relates to the use of human endeavor to
67
Romani R. and Calani Baranauskas M..
Exploring Human Computation and Social Computing to Inform the Design Process.
DOI: 10.5220/0004434300670074
In Proceedings of the 15th International Conference on Enterprise Information Systems (ICEIS-2013), pages 67-74
ISBN: 978-989-8565-61-7
Copyright
c
2013 SCITEPRESS (Science and Technology Publications, Lda.)
accomplish tasks that computers can not yet perform
is defined as “Human Computation”.
According Quinn and Bederson (2011) the
difference between human computation and social
computing is that social computing facilitates
relatively natural human behavior that happens to be
mediated by technology, whereas participation in a
human computation is directed primarily by the
human computation system. However, the same
authors show that there is an intersection field
between human computation and social computing.
This paper aims at shedding light on that
intersection field by presenting possibilities of
taking advantage of both fields to contribute to HCI
research. In this scenario, this work proposes a new
approach for supporting the choices of designers
with users’ contribution through enjoyable activities
such as games. In addition, an environment where
designers can socialize knowledge and information
in the design process is suggested.
The work is organized as follows: Section 2
presents the background research fields, delineating
the focus of interest of this paper; Section 3
organizes a preliminary literature overview in the
intersection of human computation and social
computing; Section 4 instantiates the idea proposed
with the GWIDO environment; Section 5 concludes.
2 BACKGROUND
Since the popularization of computational artefacts,
people have worked with them in several interesting
ways. More recently we have also engaged in
communicating through computers. An alternative
way to involve the human in a work process is using
their processing power to solve problems that
computers cannot yet solve. This is the modern
usage of the term “human computation” as coined
by von Ahn (2005). He yet considers that it is
feasible to solve large-scale computational problems
and collect data to teach computers basic human
talents. In fact, the idea is to put human brains
working as processors in a distributed system, each
one performing a small part of a massive
computation (von Ahn, 2009).
Human computation is related to other terms
such as collective intelligence, crowdsourcing, and
social computing but they are not synonymous
(Quinn and Bederson, 2011).
According Howe (2008) crowdsourcing is
defined as the act of conducting traditional human
work with ordinary people. An example is when a
large group of people performs a job responding to
an open call substituting a traditionally designated
agent who would perform that specific job.
On the other hand, social computing is related to
humans in social role where their communication is
mediated by technology (Parameswaran and
Whinston, 2007). Blogs, facebook ©, twiter ©, wikis
are some examples of technologies used to facilitate
the collective action and social interaction online.
Computational problems which are solved by
human computation are occasionally found in
crowdsourcing and social computing applications.
There is an intersection of crowdsourcing and
human computation issues that is shown in Figure 1.
Some applications can be classified in this
intersection such as MonoTrans which provides a
solution for the language translation task (Hu et al.,
2011).
Collective intelligence is presented in Figure 1 as
a superset of social computing, human computation
and crowdsourcing. This term is defined by Malone
et al. (2009) as groups of individuals doing things
collectively that seem intelligent. Some examples
such as Wikipedia have shown a great number of
people collaborating in the same project.
Figure 1: The intersection of Human Computation and
Social Computing can be explored in benefit of interaction
design process (adapted from Quinn and Bederson, 2011).
Although all research areas shown in Figure 1
are relevant and widely studied, this work focuses on
the intersection of Human Computation and Social
Computing. Principles of both areas can contribute
to the interface design process since we can take
advantage of the human ability to solve difficult
problems, associated to the facilities of social
ICEIS2013-15thInternationalConferenceonEnterpriseInformationSystems
68
Figure 2: Number of papers published in conferences and journals.
networks. The different on-line social networks
available on the web can enable the approximation
of both users and designers of different regions and
cultures.
With regard to Human Computation, a new set of
systems have been developed since 2004 as casual
games to collect annotations from human users; they
are called GWAPs (Game With A Purpose). The
GWAP concept was proposed by von Ahn (2006)
based on Human Computation principles. Problems
solved by humans in GWAP games have two main
assumptions: (1) computers alone are not good at
solving them and (2) they are trivial for humans.
ESP (the name is a joke with Extra Sensorial
Perception) Game was the first GWAP proposed
(von Ahn and Dabish, 2004). The ESP objective is
to label images that are considered a complex task
for computers. In this game, the same image is
presented to two players. Then, they should type
words or phrases which describe the image. Each
player does not know what the other one is typing,
but if both type exactly the same thing, this word or
phrase is a good suggestion for labelling that image.
They will again receive a new image to continue
playing. The players’ goal is to label the largest
number of images in a predefined time, getting
points every time they coincide in the answers.
GWAP is an example of collective intelligence
since this type of game aggregate data from non-
expert players helping in collective decisions that are
similar to opinions from an expert (Chamberlain et
al., 2012).
3 HUMAN COMPUTATION
AND SOCIAL COMPUTING:
A PRELIMINARY SURVEY
Several authors have explored different aspects of
Human Computation and Social Computing in the
last years (von Ahn, 2009); (Parameswaran and
Whinston, 2007); (Quinn and Bederson, 2011);
(Wang et al., 2007). With the objective of assessing
the comprisement of both areas and their
intersection, we conducted a survey on the number
of articles published about each subject in digital
libraries of ACM and IEEE since 2004. A summary
of results obtained in this search is shown in Figure
2.
The survey was conducted considering
expressions such as: "Human Computation", "Social
Computing", "GWAP", "Social Games", "Human
Computation and Social Computing", "GWAP and
Social Computing" in order to evaluate each term
separately and subsequently the association of two
main concepts.
Each expression was searched in the papers full
texts and abstracts, in both ACM and IEEE digital
libraries. The search was conducted in January 7,
2013, being restricted to articles published in
journals or conferences from 2004 to 2012. This
period was chosen considering the modern use of the
term Human Computation that started from the
proposition of the first GWAP called ESP Game
published in 2004.
Results for the terms showed that the amount of
articles about Social Computing is far superior to
that one regarding Human Computation. In part, this
ExploringHumanComputationandSocialComputingtoInformtheDesignProcess
69
Table 1: GWAPS found in literature from 2004 to 2012.
Main Purpose GWAPs Human Skill
(7) Image tagging
ESP Game (Ahn and Dabbish, 2004) Visual Recognition
Phetch (Ahn et al., 2007) Visual Recognition and Writing
KissKissBan (Ho et al., 2009) Visual Recognition, Reading and Writing
PexAce (Nagy, 2011) Visual Recognition and Writing
Karido (Steinmayr, 2011) Visual Recognition
ARTigo (Bry and Wieser, 2012) Visual Recognition
IdenticalEmotions (Aggarwal, 2012) Visual Recognition and Feelings
(7) Location-based information
Gopher Game (Casey et al., 2007) Reading, Writing and Take Pictures
Eyespy (Bell et al., 2009) Reading and Visual Recognition
Indagator (Goh et al., 2010) Reading, Writing, Walking, Take Pictures
PhotoCity (Tuite et al., 2010, 2011) Reading, Walking, Take Pictures
SPLASH (Goh et al., 2011) Reading, Writing and Visual Recognition
Tsai & Yang game (Tsai and Yang, 2011) Reading, Writing and Take Pictures
Glob (Kothandapani et al., 2012) Reading, Writing and Visual Recognition
(4) Collect common sense facts
Verbosity (Ahn et al., 2007) Reading and Writing
Rapport Game (Kuo et al., 2009) Reading, Writing and Visual Recognition
Virtual Pet Game (Kuo et al., 2009) Reading, Writing and Visual Recognition
Climate Quiz (Scharl et al., 2012) Reading and Writing
(3) Create ranking/
classifications
Matchin (Hacker and Anh, 2009) Visual recognition
Thumbs-Up (Dasdan et al., 2009) Reading and interpretation
Curator (Walsh and Golbeck, 2010) Visual recognition
(3) Natural language processing
OnToGalaxy (Krause et al., 2010) Reading and Writing
Dil Cambazı (Gencer et al, 2012) Reading
Phrase Detectives (Chamberlain et al., 2012) Reading and Interpretation
(3) Mapping users account across
social network
GameMapping (Shehab et al., 2010) Reading
Pearl & Steyvers game (Pearl and Steyvers,
2010)
Reading and Interpretation
GuessWho (Guy et al., 2011) Reading and Writing
(3) Annotating videos
OntoTube (Siorpaes and Hepp, 2008) Watching Videos and Interpretation
Popvideo (Ahn et al, 2008) Watching Videos and Interpretation
Waisda (Oomen et al., 2010) Watching Videos and Interpretation
(3) Creating ontologies or
relationships for semantic web
OntoPronto (Siorpaes and Hepp, 2008) Reading and Interpretation
SpotTheLink (Thaler et al., 2010) Reading and Interpretation
LittleSearchGame (Šimko et al., 2011) Reading and Writing
(2) Locates objects within images
Peekaboom (Ahn et al., 2006) Visual Recognition
P-HOG (Feng et al., 2012) Visual Recognition
(2) Tagging music
Tag-a-Tune (Law & Anh, 2009) Reading, Writing and Listening
Herd It (Barrington et al., 2009) Reading, Writing and Listening
(2) Generate streams of social
annotation
GiveALink Slider (Weng et al., 2011) Reading, Writing and Interpretation
Great Minds Think Alike (Weng et al., 2011) Reading, Writing and Interpretation
(1) Associate images with user
action
GWIDO Image (Romani and Baranauskas,
2009)
Visual Recognition and Interpretation
(1) Visual research and surveys Sketcharoo (Hebecker and Ebbert, 2010) Visual Recognition, Writing and Drawing
(1) Labelling game characters Shadow Shoppe (Islam et al., 2010) Visual Recognition and Interpretation
(1) Image re-targeting for
browsing images
RecognazePicture (Lux et al., 2010) Visual Recognition
(1) Colect personal data
Bake Your Personality10 (Taktamysheva et al.,
2011)
Reading
(1) Mining microblogs for
advice-oriented information
Twiage (Kleek, et al., 2012) Reading and Interpretation
result occurs because the Social Computing area has
already being widely studied since 2004. Thus, to
facilitate the display of results in the graph of Figure
2, we used logarithmic scale. Furthermore, absolute
values were also plotted in the graph. GWAP and
Social Games represent 22% and 10% of the
research developed in Human Computation and
Social Computing, respectively. Both terms are
associated with the games area.
The intersection between Human Computation
and Social Computing is still quite small since the
search engine returned only ninety articles, all
indexed by ACM and IEEE.
Moreover, when we search the terms GWAP and
Social Computing together, few articles were found
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70
(nineteen). None of the retrieved articles addresses
both terms on their abstracts. It suggests that these
two issues have not been explored jointly.
Figure 3 shows a new representation of the
survey results to present an accurate idea of the
proportion of articles published in these fields. Thus
we represent each field as a circle proportional to the
number of articles found in the search.
A survey of GWAPs found in literature since
2004 considering the ESP game as the first proposed
GWAP is presented in Table 1. GWAPs were
grouped according to their main purposes.
We consider the support to interaction and
content creation among communities of users as the
main feature of a social computing application.
In this context GWAPs can be designed as a
social computing application since the majority of
them have support of interaction among people. In
addition, by definition all GWAP produces
information. However few GWAPs exploit the
social potential for own benefit or for the benefit of
the community involved. Information generated by
GWAP usually brings benefits linked to their
purpose such as image tagging.
Figure 3: Schematic representation for the proportion of
published articles and the intersection of fields.
Table 1 highlights those GWAPs, which
explicitly promotes the communities’ formation and
generate information with some utility to these
communities. These GWAPs can be classified as
social computing applications such as Indagator,
PhotoCity, SPLASH, Gopher Game, or they make
use of information extracted from social networks
where they are inserted as for example Phrase
Detectives and GameMapping.
4 THE GWIDO ENVIRONMENT
GWIDO Image is a game proposed in 2009 with the
purpose of helping designers to make choices about
interface graphic elements (Romani and
Baranauskas, 2009; 2010). GWIDO Image is a
collaborative and synchronous two player’s GWAP
that is played in the Web at
http://gwido.nied.unicamp.br/gwido. GWIDO is an
output agreement model game. Images and texts are
its inputs provided by designers that represent
possibilities of users’ actions in Graphical User
Interfaces (GUIs). This is one of the games within
the GWIDO environment.
The GWIDO environment is a web social
application where GWIDO games can be developed
with different purposes by developers (Figure 4).
Then these games can be played by any users on the
web (Romani and Baranauskas, 2012).
Figure 4 illustrates a proposed architecture for
the environment where several GWIDOs feed a
common database. Through the GUI, designers
register graphics or sound candidates and interface
concepts associated to them into the GWIDO
environment. These elements are used in GWIDO
games. After some game rounds, the designer can
collect results verifying the most representative
images for different user profiles in the environment.
Each designer accesses only the information of
elements registered by him. In this model a
researcher can make statistical analysis to verify, for
example, whether there are regional or meaningful
differences between the different user profiles,
enabling a better informed choice of UI elements for
the system.
Figure 4: GWIDO environment architecture.
All data collected during the game can be
accessed by designers who included inputs to the
game. These data can also be shared with the
community of designers. Data gathered during the
ExploringHumanComputationandSocialComputingtoInformtheDesignProcess
71
game roles are associated with the users’ profiles to
provide accurate information to help designers in
making choices. For example, GWIDO Image
presents inputs (text and candidate images provided
by designers) and instructs the players to select the
image that best represents this text. If both players
select the same image, they get points. All choices
are registered by the game and will be available on
the environment for supporting the designer in
his/her decision process regarding which image to
use in his/her application.
The GWIDO environment is a social web
application, located in the intersection of Human
Computation and Social Computing. GWIDO
incorporates the virtuous cycle of social computing
in which the community uses a service offered by a
computational system, providing information to this
system that also uses this information to improve the
service to offer to the community (Erickson, 2013).
This is a kind of relationship in which both sides
win, what makes social computing such a productive
field.
The GWIDO environment aids at creating this
collaboration cycle between the environment and its
users (designers in this case,); GWIDO also provides
the possibility of making this cycle between
designers and prospective users of the interfaces
designed by them. In other words, when someone
plays a GWIDO game, he/she is providing
information to the designers to project new
interfaces which can be used by these own players.
In this context, GWIDO is a socio-technical
environment that may promote a culture of
participation in the design of human computer
interfaces.
5 CONCLUSIONS
When the scope of an application is well-defined
and the set of potential users is limited and
homogenous, designers have been well instrumented
in their practices. However, as the number of users
increases augmenting their differences in terms of
profiles, culture, social context, etc. the choices of
designers become much more difficult. After a
literature review on background work, this paper
presented an effort coming from the intersection of
the human computation and social computing fields,
as instrumental for supporting designers in their
choices of user interface elements. Ongoing work
involves case studies being conducted to evaluate
the effectiveness of this approach, and further work
involves a large scale test of the proposed
environment.
ACKNOWLEDGEMENTS
We thank the Brazilian funding agency CNPQ
(#560044/2010-0) for financial support to EcoWeb
Project, the IC and AFPU for funding the
registration fees and travel.
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