The Importance of Being Earnest in Crowdsourcing Systems

This paper presents the first systematic investigation of the potential performance gains for crowdsourcing systems, deriving from available information at the requester about individual worker earnestness (reputation). In particular, we first formalize the optimal task assignment problem when workers' reputation estimates are available, as the maximization of a monotone (submodular) function subject to Matroid constraints. Then, being the optimal problem NP-hard, we propose a simple but efficient greedy heuristic task allocation algorithm. We also propose a simple ``maximum a-posteriori`` decision rule. Finally, we test and compare different solutions, showing that system performance can greatly benefit from information about workers' reputation. Our main findings are that: i) even largely inaccurate estimates of workers' reputation can be effectively exploited in the task assignment to greatly improve system performance; ii) the performance of the maximum a-posteriori decision rule quickly degrades as worker reputation estimates become inaccurate; iii) when workers' reputation estimates are significantly inaccurate, the best performance can be obtained by combining our proposed task assignment algorithm with the LRA decision rule introduced in the literature.Comment: To appear at Infocom 201

A Formal Framework for Modeling Trust and Reputation in Collective Adaptive Systems

Trust and reputation models for distributed, collaborative systems have been studied and applied in several domains, in order to stimulate cooperation while preventing selfish and malicious behaviors. Nonetheless, such models have received less attention in the process of specifying and analyzing formally the functionalities of the systems mentioned above. The objective of this paper is to define a process algebraic framework for the modeling of systems that use (i) trust and reputation to govern the interactions among nodes, and (ii) communication models characterized by a high level of adaptiveness and flexibility. Hence, we propose a formalism for verifying, through model checking techniques, the robustness of these systems with respect to the typical attacks conducted against webs of trust.Comment: In Proceedings FORECAST 2016, arXiv:1607.0200

How ECS Improve Creative Use of Employees’ Knowledge?

Recently, organizations are using crowdsourcing systems (CSs) to collect innovative ideas from their employees harnessing their insights of companies’ products, processes, customers, and competitors. While crowd workers in third-party CSs are a diverse and multifaceted population with a range of motives and experience, and yet few researchers have grappled with the facilitators of the employees’ behavior comprising the creative application of their knowledge using enterprise CSs. This study develops a theoretical framework to identify enterprise CSs role and to provide the way how CSs are related to creative behavior via knowledge sharing. In this research, we used a survey to collect data from organizational employees and conducted data analysis to understand how enterprise CSs affect employees’ creative knowledge application. The findings of this study can help organization refine their ECSs and innovative initiatives