5,802 research outputs found
Accurator: Nichesourcing for Cultural Heritage
With more and more cultural heritage data being published online, their
usefulness in this open context depends on the quality and diversity of
descriptive metadata for collection objects. In many cases, existing metadata
is not adequate for a variety of retrieval and research tasks and more specific
annotations are necessary. However, eliciting such annotations is a challenge
since it often requires domain-specific knowledge. Where crowdsourcing can be
successfully used for eliciting simple annotations, identifying people with the
required expertise might prove troublesome for tasks requiring more complex or
domain-specific knowledge. Nichesourcing addresses this problem, by tapping
into the expert knowledge available in niche communities. This paper presents
Accurator, a methodology for conducting nichesourcing campaigns for cultural
heritage institutions, by addressing communities, organizing events and
tailoring a web-based annotation tool to a domain of choice. The contribution
of this paper is threefold: 1) a nichesourcing methodology, 2) an annotation
tool for experts and 3) validation of the methodology and tool in three case
studies. The three domains of the case studies are birds on art, bible prints
and fashion images. We compare the quality and quantity of obtained annotations
in the three case studies, showing that the nichesourcing methodology in
combination with the image annotation tool can be used to collect high quality
annotations in a variety of domains and annotation tasks. A user evaluation
indicates the tool is suited and usable for domain specific annotation tasks
The Dark Side of Micro-Task Marketplaces: Characterizing Fiverr and Automatically Detecting Crowdturfing
As human computation on crowdsourcing systems has become popular and powerful
for performing tasks, malicious users have started misusing these systems by
posting malicious tasks, propagating manipulated contents, and targeting
popular web services such as online social networks and search engines.
Recently, these malicious users moved to Fiverr, a fast-growing micro-task
marketplace, where workers can post crowdturfing tasks (i.e., astroturfing
campaigns run by crowd workers) and malicious customers can purchase those
tasks for only $5. In this paper, we present a comprehensive analysis of
Fiverr. First, we identify the most popular types of crowdturfing tasks found
in this marketplace and conduct case studies for these crowdturfing tasks.
Then, we build crowdturfing task detection classifiers to filter these tasks
and prevent them from becoming active in the marketplace. Our experimental
results show that the proposed classification approach effectively detects
crowdturfing tasks, achieving 97.35% accuracy. Finally, we analyze the real
world impact of crowdturfing tasks by purchasing active Fiverr tasks and
quantifying their impact on a target site. As part of this analysis, we show
that current security systems inadequately detect crowdsourced manipulation,
which confirms the necessity of our proposed crowdturfing task detection
approach
Location Privacy in Spatial Crowdsourcing
Spatial crowdsourcing (SC) is a new platform that engages individuals in
collecting and analyzing environmental, social and other spatiotemporal
information. With SC, requesters outsource their spatiotemporal tasks to a set
of workers, who will perform the tasks by physically traveling to the tasks'
locations. This chapter identifies privacy threats toward both workers and
requesters during the two main phases of spatial crowdsourcing, tasking and
reporting. Tasking is the process of identifying which tasks should be assigned
to which workers. This process is handled by a spatial crowdsourcing server
(SC-server). The latter phase is reporting, in which workers travel to the
tasks' locations, complete the tasks and upload their reports to the SC-server.
The challenge is to enable effective and efficient tasking as well as reporting
in SC without disclosing the actual locations of workers (at least until they
agree to perform a task) and the tasks themselves (at least to workers who are
not assigned to those tasks). This chapter aims to provide an overview of the
state-of-the-art in protecting users' location privacy in spatial
crowdsourcing. We provide a comparative study of a diverse set of solutions in
terms of task publishing modes (push vs. pull), problem focuses (tasking and
reporting), threats (server, requester and worker), and underlying technical
approaches (from pseudonymity, cloaking, and perturbation to exchange-based and
encryption-based techniques). The strengths and drawbacks of the techniques are
highlighted, leading to a discussion of open problems and future work
Technology for Good: Innovative Use of Technology by Charities
Technology for Good identifies ten technologies being used by charitable organizations in innovative ways. The report briefly introduces each technology and provides examples of how those technologies are being used.Examples are drawn from a broad spectrum of organizations working on widely varied issues around the globe. This makes Technology for Good a unique repository of inspiration for the public and private sectors, funders, and other change makers who support the creation and use of technology for social good
Public Participation GIS for sustainable urban mobility planning: methods, applications and challenges
Sustainable mobility planning is a new approach to planning, and as such it requires new methods of public participation, data collection and data aggregation. In the article we present an overview of Public Participation GIS (PPGIS) methods with potential use in sustainable urban mobility planning. We present the methods using examples from two recent case studies conducted in Polish cities of Poznań and Łodź. Sustainable urban mobility planning is a cyclical process, and each stage has different data and participatory requirements. Consequently, we situate the PPGIS methods in appropriate stages of planning, based on potential benefits they may bring into the planning process. We discuss key issues related to participant recruitment and provide guidelines for planners interested in implementing methods presented in the paper. The article outlines future research directions stressing the need for systematic case study evaluation
Social Turing Tests: Crowdsourcing Sybil Detection
As popular tools for spreading spam and malware, Sybils (or fake accounts)
pose a serious threat to online communities such as Online Social Networks
(OSNs). Today, sophisticated attackers are creating realistic Sybils that
effectively befriend legitimate users, rendering most automated Sybil detection
techniques ineffective. In this paper, we explore the feasibility of a
crowdsourced Sybil detection system for OSNs. We conduct a large user study on
the ability of humans to detect today's Sybil accounts, using a large corpus of
ground-truth Sybil accounts from the Facebook and Renren networks. We analyze
detection accuracy by both "experts" and "turkers" under a variety of
conditions, and find that while turkers vary significantly in their
effectiveness, experts consistently produce near-optimal results. We use these
results to drive the design of a multi-tier crowdsourcing Sybil detection
system. Using our user study data, we show that this system is scalable, and
can be highly effective either as a standalone system or as a complementary
technique to current tools
Time Critical Social Mobilization: The DARPA Network Challenge Winning Strategy
It is now commonplace to see the Web as a platform that can harness the
collective abilities of large numbers of people to accomplish tasks with
unprecedented speed, accuracy and scale. To push this idea to its limit, DARPA
launched its Network Challenge, which aimed to "explore the roles the Internet
and social networking play in the timely communication, wide-area
team-building, and urgent mobilization required to solve broad-scope,
time-critical problems." The challenge required teams to provide coordinates of
ten red weather balloons placed at different locations in the continental
United States. This large-scale mobilization required the ability to spread
information about the tasks widely and quickly, and to incentivize individuals
to act. We report on the winning team's strategy, which utilized a novel
recursive incentive mechanism to find all balloons in under nine hours. We
analyze the theoretical properties of the mechanism, and present data about its
performance in the challenge.Comment: 25 pages, 6 figure
The Use of Crowdsourcing as a Strategic Marketing Tool - An Examination of Brand Perceptions and Behavioral Intentions
The aim of this study is to understand how crowdsourcing campaigns in an online environment can change brand perceptions and behavioral intentions of non-participating customers. Therefore, the thesis connects two major concepts. First the phenomenon of crowdsourcing will be discussed with emphasis an emphasis on its use in marketing. Then crowdsourcing will be lined to the theoretical concept of con-sumer-based brand equity. The study is based on a quantitative survey in form of an experimental design, with 30 participants each in the control as well as the experi-mental group. The resulting findings indicate a partial influence of crowdsourcing campaigns on non-participants’ brand perceptions and behavioral intentions. The connection between the two concepts is strongly mediated by the customers’ famili-arity with the brand in question, though. Overall, the study contributes to the litera-ture of brand equity by extending the theoretical concept in regard to the influence of online crowdsourcing. The thesis also adds to the small research body of crowdsourcing by examining its use as a strategic marketing tool and by filling the existing research gap concerning the effects of crowdsourcing on non-participants. The results can help managers to recognize the importance of online crowdsourcing as a strategic marketing tool and to gain a better understanding of how non-participating customers perceive this tool of customer engagement
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