Related papers: TeleCrowd: A Crowdsourcing Approach to Create Info…
The wide spread of mobile devices has enabled a new paradigm of innovation called Mobile Crowdsourcing (MCS) where the concept is to allow entities, e.g., individuals or local authorities, to hire workers to help from the crowd of connected…
We present and analyze results from a pilot study that explores how crowdsourcing can be used in the process of generating distractors (incorrect answer choices) in multiple-choice concept inventories (conceptual tests of understanding). To…
Crowdsourcing models applied to work on mobile devices continuously reach new ways of solving sophisticated problems, now with a use of portable advanced devices, where users are not limited to a stationary use. There exists an open problem…
Opinions about the 2016 U.S. Presidential Candidates have been expressed in millions of tweets that are challenging to analyze automatically. Crowdsourcing the analysis of political tweets effectively is also difficult, due to large…
Crowdsourcing refers to the arrangement in which contributions are solicited from a large group of unrelated people. Due to this nature, crowdsourcers (or task requesters) often face uncertainty about the workers' capabilities which, in…
For complex crowdsourcing tasks that require collaboration between multiple individuals, teams should be formed by considering both worker compatibility and expertise. Furthermore, the nature of crowdsourcing dictates the budget for tasks…
Incentive mechanisms for crowdsourcing have been extensively studied under the framework of all-pay auctions. Along a distinct line, this paper proposes to use Tullock contests as an alternative tool to design incentive mechanisms for…
Crowdsourcing is a process of accumulating the ideas, thoughts or information from many independent participants, with aim to find the best solution for a given challenge. Modern information technologies allow for massive number of subjects…
In this paper we present a mobile crowdsourcing platform CrowdCafe, where people can perform microtasks using their smartphones while they ride a bus, travel by train, stand in a queue or wait for an appointment. These microtasks are…
Crowdsourcing is widely used to create data for common natural language understanding tasks. Despite the importance of these datasets for measuring and refining model understanding of language, there has been little focus on the…
Crowdsourcing websites (e.g. Yahoo! Answers, Amazon Mechanical Turk, and etc.) emerged in recent years that allow requesters from all around the world to post tasks and seek help from an equally global pool of workers. However, intrinsic…
Sentiment classification is a fundamental task in content analysis. Although deep learning has demonstrated promising performance in text classification compared with shallow models, it is still not able to train a satisfying classifier for…
Machine Learning competitions such as the Netflix Prize have proven reasonably successful as a method of "crowdsourcing" prediction tasks. But these competitions have a number of weaknesses, particularly in the incentive structure they…
Requirements elicitation has recently been complemented with crowd-based techniques, which continuously involve large, heterogeneous groups of users who express their feedback through a variety of media. Crowd-based elicitation has great…
In the last decade, scenario-based serious-games have become a main tool for learning new skills and capabilities. An important factor in the development of such systems is the overhead in time, cost and human resources to manually create…
Crowdsourcing and human computation has been employed in increasingly sophisticated projects that require the solution of a heterogeneous set of tasks. We explore the challenge of building or hiring an effective team, for performing tasks…
Objective: This research explores using crowdsourcing for software usability evaluation. Background: Usability studies are essential for designing user-friendly software, but traditional methods are often costly and time-consuming.…
The recent boom in crowdsourcing has opened up a new avenue for utilizing human intelligence in the realm of data analysis. This innovative approach provides a powerful means for connecting online workers to tasks that cannot effectively be…
Mobile Crowdsourcing (MCS) is the generalized act of outsourcing sensing tasks, traditionally performed by employees or contractors, to a large group of smart-phone users by means of an open call. With the increasing complexity of the…
The emergence of large language models (LLMs) has sparked much interest in creating LLM-based digital populations that can be applied to many applications such as social simulation, crowdsourcing, marketing, and recommendation systems. A…