Topic
Crowdsourcing
About: Crowdsourcing is a research topic. Over the lifetime, 12889 publications have been published within this topic receiving 230638 citations.
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TL;DR: Three online incentive mechanisms, named TBA, TOIM and TOIMAD, based on online reverse auction are designed, designed to pursue platform utility maximization, while toIM and ToIM-AD achieve the crucial property of truthfulness.
Abstract: Off-the-shelf smartphones have boosted large scale participatory sensing applications as they are equipped with various functional sensors, possess powerful computation and communication capabilities, and proliferate at a breathtaking pace Yet the low participation level of smartphone users due to various resource consumptions, such as time and power, remains a hurdle that prevents the enjoyment brought by sensing applications Recently, some researchers have done pioneer works in motivating users to contribute their resources by designing incentive mechanisms, which are able to provide certain rewards for participation However, none of these works considered smartphone users’ nature of opportunistically occurring in the area of interest Specifically, for a general smartphone sensing application, the platform would distribute tasks to each user on her arrival and has to make an immediate decision according to the user’s reply To accommodate this general setting, we design three online incentive mechanisms, named TBA, TOIM and TOIM-AD, based on online reverse auction TBA is designed to pursue platform utility maximization, while TOIM and TOIM-AD achieve the crucial property of truthfulness All mechanisms possess the desired properties of computational efficiency, individual rationality, and profitability Besides, they are highly competitive compared to the optimal offline solution The extensive simulation results reveal the impact of the key parameters and show good approximation to the state-of-the-art offline mechanism
215 citations
12 Aug 2012
TL;DR: This paper proposes and investigates a new methodology for discovering topic experts in the popular Twitter social network that leverages Twitter Lists, which is often carefully curated by individual users to include experts on topics that interest them and whose meta-data provides valuable semantic cues to the experts' domain of expertise.
Abstract: Finding topic experts on microblogging sites with millions of users, such as Twitter, is a hard and challenging problem. In this paper, we propose and investigate a new methodology for discovering topic experts in the popular Twitter social network. Our methodology relies on the wisdom of the Twitter crowds -- it leverages Twitter Lists, which are often carefully curated by individual users to include experts on topics that interest them and whose meta-data (List names and descriptions) provides valuable semantic cues to the experts' domain of expertise. We mined List information to build Cognos, a system for finding topic experts in Twitter. Detailed experimental evaluation based on a real-world deployment shows that: (a) Cognos infers a user's expertise more accurately and comprehensively than state-of-the-art systems that rely on the user's bio or tweet content, (b) Cognos scales well due to built-in mechanisms to efficiently update its experts' database with new users, and (c) Despite relying only on a single feature, namely crowdsourced Lists, Cognos yields results comparable to, if not better than, those given by the official Twitter experts search engine for a wide range of queries in user tests. Our study highlights Lists as a potentially valuable source of information for future content or expert search systems in Twitter.
215 citations
26 Apr 2010
TL;DR: It is found that individual specific traits together with the project payment and the number of project requirements are significant predictors of the final project quality, and significant evidence of strategic behavior of contestants is found.
Abstract: Crowdsourcing is a new Web phenomenon, in which a firm takes a function once performed in-house and outsources it to a crowd, usually in the form of an open contest.Designing efficient crowdsourcing mechanisms is not possible without deep understanding of incentives and strategic choices of all participants.This paper presents an empirical analysis of determinants of individual performance in multiple simultaneous crowdsourcing contests using a unique dataset for the world's largest competitive software development portal: TopCoder.com. Special attention is given to studying the effects of the reputation system currently used by TopCoder.com on behavior of contestants. We find that individual specific traits together with the project payment and the number of project requirements are significant predictors of the final project quality. Furthermore, we find significant evidence of strategic behavior of contestants. High rated contestants face tougher competition from their opponents in the competition phase of the contest. In order to soften the competition, they move first in the registration phase of the contest, signing up early for particular projects. Although registration in TopCoder contests is non-binding, it deters entry of opponents in the same contest; our lower bound estimate shows that this strategy generates significant surplus gain to high rated contestants. We conjecture that the reputation + cheap talk mechanism employed by TopCoder has a positive effect on allocative efficiency of simultaneous all-pay contests and should be considered for adoption in other crowdsourcing platforms.
215 citations
05 Oct 2014
TL;DR: It is demonstrated that Foundry and flash teams enable crowdsourcing of a broad class of goals including design prototyping, course development, and film animation, in half the work time of traditional self-managed teams.
Abstract: We introduce flash teams, a framework for dynamically assembling and managing paid experts from the crowd. Flash teams advance a vision of expert crowd work that accomplishes complex, interdependent goals such as engineering and design. These teams consist of sequences of linked modular tasks and handoffs that can be computationally managed. Interactive systems reason about and manipulate these teams' structures: for example, flash teams can be recombined to form larger organizations and authored automatically in response to a user's request. Flash teams can also hire more people elastically in reaction to task needs, and pipeline intermediate output to accelerate completion times. To enable flash teams, we present Foundry, an end-user authoring platform and runtime manager. Foundry allows users to author modular tasks, then manages teams through handoffs of intermediate work. We demonstrate that Foundry and flash teams enable crowdsourcing of a broad class of goals including design prototyping, course development, and film animation, in half the work time of traditional self-managed teams.
214 citations
TL;DR: A framework for a company-internal application of crowdsourcing methods is proposed and a set of five goals companies can pursue employing internal crowdsourcing are presented.
Abstract: Crowdsourcing is typically associated with the incorporation of company-external stakeholders such as customers in the value creating process. This article proposes a framework for a company-internal application of crowdsourcing methods. It presents a set of five goals companies can pursue employing internal crowdsourcing. The practical approach of an Austrian medium-sized technology company is described in detail, including insights on software design and appropriate procedures.
214 citations