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Showing posts with the label gianluca demartini

Alessandro Checco & Jo Bates win Best Paper at HCOMP 2018

From Director of Research Professor Paul Clough: I am delighted to announce that Alessandro Checco and Jo Bates (together with Gianluca Demartini) have won the Best Paper award at the prestigious Human Computation or HCOMP 2018 conference for the following paper: Checco A, Bates J & Demartini G (2018) All That Glitters is Gold -- An Attack Scheme on Gold Questions in Crowdsourcing. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing. Abstract here; http://eprints.whiterose.ac.uk/130654/ Not only is it a significant achievement to even be accepted at this conference it is an outstanding achievement to be nominated for Best Paper and then to win it is incredible. Alessandro and Gianluca were awarded the prize at HComp 2018 . Alessandro had this to say about the paper and reviews: "Feedback from chairs was that they really liked the fact we opened a new direction (that is having workers using ML solutions on the employers). We will have the opportu...

Ahmed, Bath and Demartini book chapter on challenges of researching Twitter now Open Access

PhD student Wasim Ahmed, Professor Peter Bath, and Dr Gianluca Demartini have recently had a peer-reviewed book chapter published which looked at the ethical, legal, and methodological challenges of researching Twitter. The chapter is now open access, and the abstract and the link to download the chapter are provided below. Abstract This chapter provides an overview of the specific legal, ethical, and privacy issues that can arise when conducting research using Twitter data. Existing literature is reviewed to inform those who may be undertaking social media research. We also present a number of industry and academic case studies in order to highlight the challenges that may arise in research projects using social media data. Finally, the chapter provides an overview of the process that was followed to gain ethics approval for a Ph.D. project using Twitter as a primary source of data. By outlining a number of Twitter-specific research case studies, the chapter will be a valuable res...