Engaging Social Medias: Case Mobile Crowdsourcing
Yefeng Liu1, Vili Lehdonvirta2, Todorka Alexandrova1, Ming Liu1, Tatsuo Nakajima1
1
Dept. of Computer Science
Waseda University
Tokyo, Japan
{yefeng, toty, akiralm, tatsuo}
@dcl.info.waseda.ac.jp
2
Helsinki Institute for
Information Technology
Helsinki, Finland
vili.lehdonvirta@hiit.fi
ABSTRACT
In this paper we present an attempt of engaging social media
population for bringing crowdsourcing model into a mobile
context. The proposed social media crowdsourcing plat-
form leverages the existing social networking applications
to rapidly allocate microtasks to a wide network of crowd-
workers, and visualizes the geotagged result data in order
to create a sort of visual information pool for public use.
Activating participation is the critical success factor of so-
cial media engagement, and it is a significant challenge for
researchers and practitioners to find ways to engage and di-
rect the participants’ attention to useful purposes. In this
paper, we review three approaches to incentivising engage-
ment in social media, especially mobile social media: the
game-based incentives, the social psychological incentives,
and the economic incentives. Their use and measurement
is examined in the context of a specific application, a mo-
bile social search system. A prototype system and its user
study are described. The results will contribute to the un-
derstanding of engagement and incentives in mobile social
media.
Categories and Subject Descriptors
H.5.m [Information interfaces and presentation (e.g.,
HCI)]: Miscellaneous; H.4.0 [Information systems ap-
plications]: General; H.1.2 [User/Machine Systems]:
Human factors
General Terms
Design; Human Factors
Keywords
Social media engagement, crowdsourcing, human computa-
tion, incentive mechanism, mobile social search
1. INTRODUCTION
Permission to make digital or hard copies of all or part of this work for
personal or classroom use is granted without fee provided that copies are
not made or distributed for profit or commercial advantage and that copies
bear this notice and the full citation on the first page. To copy otherwise, to
republish, to post on servers or to redistribute to lists, requires prior specific
permission and/or a fee.
SoME ’11, March 28, 2011, Hyderabad, India
Copyright c￿2011 ACM xxx-x-xxxx-xxxx-xxx $10.00
Smartphones define a trend towards increasing combination
and integration of computing, sensing, and positioning capa-
bilities with almost ubiquitous interconnectivity. Which in
consequence facilitates the implementation of rich-content
mobile social networking applications. Result in a mobile
and social computing infrastructure that will benefit both
users and technology providers by engaging more potential
content contributors. The purpose of this line of research
is to examine how to engage social media population in or-
der to effortlessly bring the crowdsourcing application into
a mobile context.
Crowdsourcing is the act of outsourcing tasks, traditionally
performed by an employee or contractor, to a large group
of Internet population (the wise crowd) by means of an
open call. The potential of mixing mobile technologies and
crowdsourcing offers vaster resources of computation. For
instance, in nowadays urban areas it is common that people
allot a large amount of time for commuting or waiting for
various events. Thereby, their time is actually fragmented
into numerous small pieces of time and most of them are oc-
cupied with meaningless activities. We believe that, in this
case, the crowdsourcing model provides a win-win solution
for better use of this time by engaging people through their
networked and ubiquitous mobile devices. However, most of
the current human computation and crowdsourcing systems
(e.g., Amazon Mechanical Turk [1]) are passive services that
are using worker-pull strategy to allocate tasks, and require
relatively complex operation to create a new task. Hence
such systems fail to adapt to the mobile context where users
require simple input method and rapid response.
In this paper we introduce a crowdsourcing platform de-
signed for mobile users. Our design principle is simple: build
the system around existing social media platforms — the
popular services that inherently have the culture of sharing
and participation, and are already well known and used by a
large and growing number of users. Diverse mobile applica-
tions are available for job providers to handily create a task.
Tasks are delivered to appropriate members in a community
of voluntary participants, in the form of an open call, via
different social media platforms (Twitter, Facebook, Mixi,
etc.) and email. If suitable, the geotagged result data may
also be visualized on social mapping tools (e.g., Ushahidi [6])
and/or argument reality platforms (e.g., Sekai Camera [5]),
result in an information pool that creates a public good.
Activating participation is the critical success factor of social

media engagement, and it is a significant challenge for re-
searchers and practitioners to find ways to engage and direct
the participants’ attention to useful purposes. In this paper,
we review three approaches to incentivising engagement in
social media, especially mobile social media: the game-based
incentives, the social incentives and the economic incentives.
Additionally, we discuss how the crowdworkers’ various cul-
tural backgrounds may affect their incentive preferences.
Their use and measurement is examined in the context of
a case study, UbiAsk system. A prototype and user study
of UbiAsk are described.
2. MOBILECROWDSOURCINGPLATFORM
We present a mobile crowdsourcing platform, in which the
ubiquitous users in the cloud can rapidly create, deliver,
perform the microtasks and share the results via different
social medias.
WůĂƞŽƌŵ
API
etc. etc.
Location-based Result Data Representation & Reusage
Requesters Crowdworkers
etc.
Figure 1: Platform System Architecture
Figure 1 illustrates the basic system architecture. Diverse
methods can be utilized by the job provider to quickly cre-
ate and submit a task to the server. Proxy server pushes
the task to appropriate workers via emails as well as dif-
ferent social media platforms such as Twitter or Facebook.
We argue that the results may be not only valuable for the
original requester but also beneficial to a broader public.
Thereby, optionally, the location based result data can be
visualized with other social mapping platforms and/or so-
cial augmented reality services.
A significant distinction between this platform and other
mobile crowdsourcing systems (e.g., [14]) is that the work
assignments in the system also originate from a crowd of
numerous mobile users rather than contracting companies
or individuals.
3. PARTICIPATION INCENTIVES
How to design appropriate motivational mechanisms to pro-
mote active participation is known to be the critical factor
of social media engagement. Previous studies in social and
computer science have identified a list of approaches to mo-
tivate social engagements [9, 13]. In this paper we focus on
three main approaches among others: the game-based in-
centives, the social incentives, and the economic incentives.
The purpose of this section is not to give a ranking of the
methods. Instead, we advocate for an appropriate exercise
of the different motivational mechanisms, depending on the
particular usage or application domain of the platform.
3.1 Game Based Incentives
The idea of taking entertaining and engaging elements from
computer games and using them to incentivise participation
in other contexts is increasingly studied in a variety of fields.
In education, the approach is known as “serious games” [23]
and in human computing it is sometimes called “games with
a purpose” [20]. Most recently, digital marketing and social
media practitioners have adopted this approach under the
term “gamification” [22]. The idea is to make a task en-
tertaining, like a on-line game, thus making it possible to
engage people to conscientiously perform tasks. The valu-
able output data itself is actually generated as a byproduct
by the game. However, on the other hand, the difficulty
of designing such a game is also a well known problem. In
many situations the tasks can be too boring or complicated
to turn into any game that is actually enjoyable or fun to
play. There is no consensus on how to measure the effect of
game elements in social media application, but traditional
measures such as use frequency and usage time are applica-
ble.
The ESP game [3] is one of the most famous examples of this
kind. Players are paired in the game and they need to give
relevant descriptions for a given image. If the description
matched with other player’s answer, players win and score
the points, otherwise lose. The real purpose of the game is
to rapidly collect annotations for a large number of images.
Thereafter, various games have been devised in the style of
ESP game. Arase et al. [8] proposed a web-based multi-
player game to collect knowledge on the geographical rele-
vance of images, in order to better represent certain images’
geographical context for searching and browsing. Other than
the casual games, Markus Krause et al. [16] implemented a
relatively complex action game OnToGalaxy in the context
of human computation. In their design the task is hidden in
the gameplay that it is no longer perceived as a dominant
element of the game.
3.2 Social Incentives
Social psychological, such as social facilitation effect or so-
cial loafing, is another widely harnessed non-monetary in-
centive mechanism to promote increased contributions to
on-line systems. Social facilitation effect [21] refers to the
tendency of people perform better on simple tasks while un-
der someone else’s watching, rather than while they are alone
or when they are working alongside other people. On the
other hand, the social loafing effect [17] is the phenomenon of
people making less effort to achieve a goal when they work in
a group than when they work alone, since they feel their con-
tributions do not count, are not evaluated or valued. This
is seen as one of the main reasons group are less productive
than the combined performance of members working alone.
Ways of taking the advantage of the positive social facili-
tation and avoiding the negative social loafing in for online
data collection systems were suggested in [7]: individuals’
efforts should be prominently displayed, individuals should
know that their work can easily be evaluated by others, and
the unique value of each individual’s contribution should be