Reputation Management in Crowdsourcing Systems

Allahbakhsh, Mohammad; Ignjatović, Aleksandar; Benatallah, Boualem; Beheshti, Amin; Bertino, Elisa; Foo, Norman Y.

doi:10.4108/icst.collaboratecom.2012.250499

Cited by 62 publications

(41 citation statements)

References 13 publications

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“…For social networks and crowdsourcing platforms it is already identified that trust is important in deciding with whom to establish connections and with whom to interact [8], [22], [2]. We stress that this importance is even higher in SCUs because they entail complex, structures and organized work.…”

Section: Introductionmentioning

confidence: 89%

“…As far as we know, online social trust in the context of Human Computation [14] is only explicitly investigated in the context of social networks such as in [22] and [8], the Crowdsourcing context [2], as well as in human-enhanced service oriented environments on individual worker-basis [16]. However, there is no trust investigation based on metrics relevant for task-executing elastic collectives of human based services such as SCUs, although there is some work on trust in virtual teams (e.g., [9]).…”

Section: Introductionmentioning

confidence: 99%

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Trust-Aware Elastic Social Compute Units

Riveni

Truong

Dustdar

2015

2015 IEEE Trustcom/BigDataSE/Ispa

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Abstract-With the advance of research in human computation, applications and software systems are increasingly being designed to include the human aspect of computation. We work with Social Compute Units (SCUs) that are computational constructs with people as their core resources who use software services to organize and conduct their work. SCUs are collaborative units, and have a cloud-like behavior in the sense that they are elastically provisioned and adapted at runtime. Systems that utilize the concept of SCUs bring challenges that are associated with the highly dynamic and unpredictable human-centric behavior. Thus, trust in human based services is of paramount importance. While there is related work on social trust in the social networking and crowdsourcing areas, trust in highly coordinated constructs such as SCUs remains a significant challenge. In this paper we provide a trust model that considers merging social trust with performance-based trust of human based services into an integrated trust model for SCUs. We illustrate the models' application in concrete strategies, such as for elastic management of SCUs and incentives for SCU members.

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Section: Introductionmentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Trust-Aware Elastic Social Compute Units

Riveni

Truong

Dustdar

2015

2015 IEEE Trustcom/BigDataSE/Ispa

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“…Quality in crowdsourcing is always under question. The reason is that workers in crowdsourcing systems have different levels of expertise and experiences; they contribute with different incentives and motivations; and even they might be included in collaborative unfair activities [33,42,43]. Several approaches are proposed to assess quality of workers' contributions such as expert review, input agreement, output agreement, majority consensus and ground truth [33].…”

Section: Dimensionsmentioning

confidence: 99%

Crowd-Enhanced Cloud Services: Issues and Directions

Arbabi¹,

Bakhsh²,

Sharifi³

2015

IJCA

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Cloud computing systems have emerged as a type of distributed systems in which a multitude of interconnected machines are gathered and recruited over the internet to help solve a computation or data-intensive problem. There are large numbers of cases in which Cloud techniques solely are not able to solve the job due to the nature of the tasks. To overcome this problem recently a strong inclination has emerged towards enlisting the human intelligence and wisdom of crowds a.k.a. Crowdsourcing in combination with the machine automated techniques. In this paper the authors propose a model for integrating crowds of people in the Cloud environments to enrich Cloud computing environments to be able to provide hybrid human-machine services enabling it to solve a wider variety of problems which some of them are studied here. The authors nickname these rich types of services, Crowd-enhanced Cloud services. At the end, the modality and challenges of this convergence and its future trends are explored.

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“…The reputation score and expertise of workers are built based on the history of a participant, i.e., the quality of contributions of the participant in the previous tasks. Since the number of accomplished tasks for such a participant is small, the parameters and attributes that are computed based on such a short or sparse history should have a lower credibility [2]. Recall that is the engagement probability of a the participant .…”

Section: Recruitment Unitmentioning

confidence: 99%

A Task Decomposition Framework for Surveying the Crowd Contextual Insights

Allahbakhsh

Arbabi

Shirazi

et al. 2015

2015 IEEE 8th International Conference on Service-Oriented Computing and Applications (SOCA)

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Polls, as the most common method of eliciting crowd insights are getting more and more popular. From predicting election results, to customer satisfaction, to scientific surveys, polls play a crucial rule in revealing the true sentiment of a community. However, when participation in a poll is subject to having some specific expertise and skills, finding sufficient number of participants for a given poll is a serious challenge.In this paper, we propose a new method of polling crowd contextual insight which is based on decomposing a poll into some sub-polls and recruiting participants to answer the given questions. We also take into account the probability of engagement of a participant in a poll to make sure that we recruit sufficient number of suitable workers.The proposed method is implemented and tested using the simulated data, build based on a public data dump from Stackoverflow. The evaluation results show the superiority of our proposed method over the other related work.

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Reputation Management in Crowdsourcing Systems

Cited by 62 publications

References 13 publications

Trust-Aware Elastic Social Compute Units

Trust-Aware Elastic Social Compute Units

Crowd-Enhanced Cloud Services: Issues and Directions

A Task Decomposition Framework for Surveying the Crowd Contextual Insights

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