Near-Optimally Teaching the Crowd to Classify

How should we present training examples to learners to teach them classification rules? This is a natural problem when training workers for crowdsourcing labeling tasks, and is also motivated by challenges in data-driven online education. We propose a natural stochastic model of the learners, modeling them as randomly switching among hypotheses based on observed feedback. We then develop STRICT, an efficient algorithm for selecting examples to teach to workers. Our solution greedily maximizes a submodular surrogate objective function in order to select examples to show to the learners. We prove that our strategy is competitive with the optimal teaching policy. Moreover, for the special case of linear separators, we prove that an exponential reduction in error probability can be achieved. Our experiments on simulated workers as well as three real image annotation tasks on Amazon Mechanical Turk show the effectiveness of our teaching algorithm

Trump, Propaganda, and the Politics of Ressentiment

This article frames Trump's politics through a genealogy of propaganda, going back to P.T. Barnum in the 19th century and moving through the crowd psychologist Gustave Le Bon and the public relations counsel Edward Bernays in the 20th. This genealogy shows how propaganda was developed as a tool by eager professionals who would hire themselves to the elite to control the masses. Trump’s propaganda presents a break in that he has not only removed professionals from control over his propaganda, he has mobilized it as a force against them. His lower and middle class supporters may not materially gain from Trump’s politics, but they get to vent their ressentiment on the professional class and see them too become the targets of propagandistic control. Ultimately, the conflict between working class whites, those without college degrees, and professionals earns little for its participants and occludes the role that elites play in class dynamics in the United States. This article adds substance and context to the claims that Trump’s appeal is anti-professional while showing that the claims that his supporters are ‘voting against their interests’ does not reflect the real psychological benefits many Trumpists get from supporting him

Understanding Communication Patterns in MOOCs: Combining Data Mining and qualitative methods

Massive Open Online Courses (MOOCs) offer unprecedented opportunities to learn at scale. Within a few years, the phenomenon of crowd-based learning has gained enormous popularity with millions of learners across the globe participating in courses ranging from Popular Music to Astrophysics. They have captured the imaginations of many, attracting significant media attention - with The New York Times naming 2012 "The Year of the MOOC." For those engaged in learning analytics and educational data mining, MOOCs have provided an exciting opportunity to develop innovative methodologies that harness big data in education.Comment: Preprint of a chapter to appear in "Data Mining and Learning Analytics: Applications in Educational Research

Rethinking the practice of accountability journalism in the digital age. The inception and development of the first Portuguese university-based investigative journalism centre and whistleblowing platform

At a time of worrying change, when Western traditional media outlets appear to be engulfed by the collapse of the advertising-based business model and can hardly bear the strain brought about by new technologies, the present study identifies an increasing information deficit as regards quality accountability reporting. Taking up Duffield and Cokley’s challenge to change in response to the demands of the time, the present paper supports the development of VALQUIRIA, at https://valquiria.org, a transmedia, multiplatform investigative journalism project integrated in the Faculty for Humanities and Social Sciences of the NOVA University of Lisbon. Valquíria, adopting a new sustainable media model, represents the very first attempt in Portugal to create a completely independent space for the education of investigative journalists, the assistance to foreign and local reporters, the production and diffusion of accountability reporting, technological products and innovative practices which can aid the profession. Featuring a vibrant crowd-sourcing and collaborative policy, its ultimate aim is to reinvigorate and enhance the practice of accountability journalism in Portugal, proving its urgency for preserving and guarding a healthy democracy. To change even more the traditional paradigm of public interest journalism, the project features a whistleblowing platform called PTLeaks: built in cooperation with the HERMES Center for Transparency and Digital Human rights, it is the first Portuguese GlobaLeaks initiative applied to investigative journalism