Related papers: Next Generation Crowdsourcing for Collective Intel…
What is the state of the literature in respect to Crowdsourcing for policy making? This work attempts to answer this question by collecting, categorizing, and situating the extant research investigating Crowdsourcing for policy, within the…
Artificial Intelligence of Things (AIoT) is an emerging frontier based on the deep fusion of Internet of Things (IoT) and Artificial Intelligence (AI) technologies. Although advanced deep learning techniques enhance the efficient data…
Crowdsourcing enables one to leverage on the intelligence and wisdom of potentially large groups of individuals toward solving problems. Common problems approached with crowdsourcing are labeling images, translating or transcribing text,…
As the population of world is increasing, and even more concentrated in urban areas, ensuring public safety is becoming a taunting job for security personnel and crowd managers. Mass events like sports, festivals, concerts, political…
Internet-connected smart devices are increasing at an exponential rate. These powerful devices have created a yet-untapped pool of idle resources that can be utilised, among others, for processing data in resource-depleted environments. The…
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…
Many companies now use crowdsourcing to leverage external (as well as internal) crowds to perform specialized work, and so methods of improving efficiency are critical. Tasks in crowdsourcing systems with specialized work have multiple…
There has been significant interest in crowdsourcing and human computation. One subclass of human computation applications are those directed at tasks that involve planning (e.g. travel planning) and scheduling (e.g. conference scheduling).…
Growing apprehensions surrounding public safety have captured the attention of numerous governments and security agencies across the globe. These entities are increasingly acknowledging the imperative need for reliable and secure…
The main goal of this paper is to discuss how to integrate the possibilities of crowdsourcing platforms with systems supporting workflow to enable the engagement and interaction with business tasks of a wider group of people. Thus, this…
Crowd counting is an effective tool for situational awareness in public places. Automated crowd counting using images and videos is an interesting yet challenging problem that has gained significant attention in computer vision. Over the…
Untile recently crowdsourcing has been primarily conceived as an online activity to harness resources for problem solving. However the emergence of opportunistic networking (ON) has opened up crowdsourcing to the spatial domain. In this…
Crowd sensing is a new paradigm which leverages the pervasive smartphones to efficiently collect and upload sensing data, enabling numerous novel applications. To achieve good service quality for a crowd sensing application, incentive…
Crowdsourcing has emerged as a powerful paradigm for efficiently labeling large datasets and performing various learning tasks, by leveraging crowds of human annotators. When additional information is available about the data,…
Crowdsourcing is a favorable computing paradigm for processing computer-hard tasks by harnessing human intelligence. However, generic crowdsourcing systems may lead to privacy-leakage through the sharing of worker data. To tackle this…
This paper argues for recognizing an emerging paradigm of causal learning by wisdom of the crowd. Recent developments in government, industry, and research point to the rise of decentralized and crowd-based approaches within causal…
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…
Smart devices with built-in sensors, computational capabilities, and network connectivity have become increasingly pervasive. The crowds of smart devices offer opportunities to collectively sense and perform computing tasks in an…
Crowdsourcing utilizes the wisdom of crowds for collective classification via information (e.g., labels of an item) provided by labelers. Current crowdsourcing algorithms are mainly unsupervised methods that are unaware of the quality of…
In this work we seek to understand how differences in location affect participation outcomes in IT-mediated crowds. To do so, we operationalize Crowd Capital Theory with data from a popular international creative crowdsourcing site, to…