Post, Mine, Repeat Social Media Data Mining Becomes Ordinary
'Post, Mine, Repeat is a genuinely ground-breaking and original piece of work, in which Helen Kennedy shares a range of important and revealing empirical insights into the practices of data mining. To my knowledge, no-one before has managed to produce suc
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HELEN KENNEDY
Post, Mine, Repeat
Helen Kennedy
Post, Mine, Repeat Social Media Data Mining Becomes Ordinary
Helen Kennedy Department of Sociological Studies University of Sheffield Sheffield, UK
ISBN 978-1-137-35397-9 ISBN 978-1-137-35398-6 DOI 10.1057/978-1-137-35398-6
(eBook)
Library of Congress Control Number: 2016938708 © The Editor(s) (if applicable) and The Author(s) 2016 The author(s) has/have asserted their right(s) to be identified as the author(s) of this work in accordance with the Copyright, Designs and Patents Act 1988. This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Palgrave Macmillan imprint is published by Springer Nature The registered company is Macmillan Publishers Ltd. London
ACKNOWLEDGEMENTS
Much of the research discussed in this book received funding from UK Research Councils and from other sources, and for this I’m very grateful. Thanks to funders as follows: • The Arts and Humanities Research Council (AHRC), which supported ‘Understanding Social Media Monitoring’ (Grant AH/ L003775) with a Research Fellowship. This funding made possible the research discussed in Chapter 6, some of the research discussed in Chapter 8, and the writing of this book. • The Engineering and Physical Sciences Research Council (EPSRC), which supported ‘Digital Data Analysis, public engagement and the social life of methods’ (Grant 95575108) and ‘Public Engagement and Cultures of Expertise’ (Grant EPSRC-CCN2013-LEEDS), discussed in Chapter 4. • Various small grants from the University of Leeds, including: – HEIF V (Higher Education Innovation Fund, Reference 95559240) – IGNITE (References 95559274 and 95559274) – The Creative and Cultural Industries Exchange (Reference 95559284). These grants funded interviews in social media data mining companies, discussed in Chapter 5, and focus groups with social media users, discussed in Chapter 7. v
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ACKNOWLEDGEMENTS
Some of the material in this book is derived in
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