Related papers: Crowdsourcing through Cognitive Opportunistic Netw…
The increased use of online social networks for the dissemination of information comes with the misuse of the internet for cyberbullying, cybercrime, spam, vandalism, amongst other things. To proactively identify abuse in the networks, we…
Information garnered from activity on location-based social networks can be harnessed to characterize urban spaces and organize them into neighborhoods. In this work, we adopt a data-driven approach to the identification and modeling of…
Crowdsourcing has been successfully applied in many domains including astronomy, cryptography and biology. In order to test its potential for useful application in a Smart Grid context, this paper investigates the extent to which a crowd…
Crowd-intelligence tries to gather, process, infer and ascertain massive useful information by utilizing the intelligence of crowds or distributed computers, which has great potential in Industrial Internet of Things (IIoT). A…
In this paper, we consider the problem of incentive mechanism design for smart-phone crowd-sourcing. Each user participating in crowd-sourcing submits a set of tasks it can accomplish and its corresponding bid. The platform then selects the…
With rapid e-commerce growth, on-demand urban delivery is having a high time especially for food, grocery, and retail, often requiring delivery in a very short amount of time after an order is placed. This imposes significant financial and…
The evolution of AI is advancing rapidly, creating both challenges and opportunities for industry-community collaboration. In this work, we present a novel methodology aiming to facilitate this collaboration through crowdsourcing of AI…
The problem of "approximating the crowd" is that of estimating the crowd's majority opinion by querying only a subset of it. Algorithms that approximate the crowd can intelligently stretch a limited budget for a crowdsourcing task. We…
We investigate crowdsourcing algorithms for finding the top-quality item within a large collection of objects with unknown intrinsic quality values. This is an important problem with many relevant applications, for example in networked…
Crowdsourcing offers unprecedented potential for solving tasks efficiently by tapping into the skills of large groups of people. A salient feature of crowdsourcing---its openness of entry---makes it vulnerable to malicious behavior. Such…
Crowdsourcing is rapidly evolving and applied in situations where ideas, labour, opinion or expertise of large groups of people are used. Crowdsourcing is now used in various policy-making initiatives; however, this use has usually focused…
Crowdsensing is a promising sensing paradigm for smart city applications (e.g., traffic and environment monitoring) with the prevalence of smart mobile devices and advanced network infrastructure. Meanwhile, as tasks are performed by…
The aim of this paper is to demonstrate that the current understanding of crowdsourcing may not be broad enough to capture the diversity of crowd work during disasters, or specific enough to highlight the unique dynamics of information…
The phenomenal success of certain crowdsourced online platforms, such as Wikipedia, is accredited to their ability to tap the crowd's potential to collaboratively build knowledge. While it is well known that the crowd's collective wisdom…
Crowdsourcing is beginning to be used for policymaking. The wisdom of crowds [Surowiecki 2005], and crowdsourcing [Brabham 2008], are seen as new avenues that can shape all kinds of policy, from transportation policy [Nash 2009] to urban…
Crowdsourcing is an easy, cheap, and fast way to perform large scale quality assessment; however, human judgments are often influenced by cognitive biases, which lowers their credibility. In this study, we focus on cognitive biases…
Crowdsourcing can identify high-quality solutions to problems; however, individual decisions are constrained by cognitive biases. We investigate some of these biases in an experimental model of a question-answering system. In both natural…
As mobile crowdsensing techniques are steering many smart-city applications, an incentive scheme that motivates the crowd to actively participate becomes a key to the success of such city-scale applications. This paper presents a…
In this work, we initiate the investigation of optimization opportunities in collaborative crowdsourcing. Many popular applications, such as collaborative document editing, sentence translation, or citizen science resort to this special…
An important aspect of urban planning is understanding crowd levels at various locations, which typically require the use of physical sensors. Such sensors are potentially costly and time consuming to implement on a large scale. To address…