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CROWDWORK, CRISIS AND CONVERGENCE: HOW THE CONNECTED CROWD ORGANIZES INFORMATION DURING MASS DISRUPTION EVENTS by KATE STARBIRD B.S., Stanford University, 1997 A thesis submitted to the Faculty of the Graduate School of the University of Colorado in partial fulfillment of the requirement for the degree of Doctor of Philosophy Technology, Media and Society Alliance for Technology, Learning and Society (ATLAS) Institute 2012 This dissertation entitled: Crowdwork, Crisis and Convergence: How the Connected Crowd Organizes Information during Mass Disruption Events written by Kate Starbird has been approved for the Alliance for Technology, Learning and Society Institute Leysia Palen John Bennett Edwin Hutchins Michele Jackson Clayton Lewis Date The final copy of this thesis has been examined by the signatories, and we Find that both the content and the form meet acceptable presentation standards Of scholarly work in the above mentioned discipline. IRB protocols #10-0456 and #0407.15 ABSTRACT OF THE DISSERTATION By Kate Starbird (Ph.D. Technology, Media and Society; ATLAS Institute) Crowdwork, Crisis and Convergence: How the Connected Crowd Organizes Information during Mass Disruption Events Dissertation Directed by Associate Professor Leysia Palen Social media have experienced widespread adoption in recent years. Though designed and appropriated for a range of purposes, users are consistently turning to these platforms during times of crisis and mass disruption—a term used here to characterize events, including mass emergencies, natural disasters and political protests, that cause significant disruption to normal routines. Social media are playing host to new, digital forms of the social convergence behavior long known to occur in the wake of crisis events. This activity, which includes participation from local citizens, emergency responders, and global onlookers alike, produces huge volumes of data, some with potential value to affected people and responders. It also creates new challenges. Noise, misinformation, lost context and the unstructured nature of social media updates all contribute to an emerging information processing problem, with information seekers forced to “drink from the firehose” to identify the data they need. Noting the difficulties of completely solving this problem with purely computational solutions, I address the challenge of processing social media updates into usable information from a perspective that positions the participating crowd as an asset in the effort. At the center of this inquiry is the discovery of an emerging role for remote participants during mass disruption events—that of the digital volunteer. This dissertation consists of four separate studies of digital volunteerism and other forms of remote participation, examining several ways members of the remote crowd help to organize information during mass disruption events. Across the different studies, I employ a mixture of methods, including qualitative and quantitative analysis of large volumes of Twitter data, interviews with digital volunteers, and participant observation within a virtual volunteer organization. iii Integrating the findings from these separate studies, I introduce a new term, crowdwork, to describe the productive activity of remote participants during mass disruption events. Throughout, this dissertation works to unpack the popular crowdsourcing term, by identifying salient features of crowdwork in this context and comparing those with current understandings of crowdsourcing. Examining the larger ecosystem of digital volunteerism during mass disruption events, I describe crowdwork in this context as a multilevel filtration system, explaining how information is processed through a variety of different activities at different layers within a complex information space that includes crowdworkers, virtual organizations, and social media sites that host both the information and the information processing. This model identifies several potential “sites” of innovation where computational algorithms could both support and leverage crowdwork. Finally, from another perspective, I examine crowdwork through the movement and transformation of information. Using the theory of distributed cognition in combination with this information-centered approach, this dissertation concludes with a holistic view of crowdwork on social media platforms as collective intelligence manifested within a global cognitive system. iv ACKNOWLEDGMENTS This work would not have been possible without the support of many individuals and organizations. First, I would like to thank my advisor and mentor, Leysia Palen, for all of her direction, support, encouragement, and advice during my time at the University of Colorado. There is not a chance that I would be researching in this crisis informatics space if I had not connected with her early in my graduate career, and it’s questionable whether or not I would have taken my PhD studies to their conclusion without her guidance. I am extremely grateful to her for investing her time and energy into molding me into the researcher and scholar that I have become (or rather am still and always will be becoming). Along that same vein, I would like to thank all my colleagues at Project EPIC for the conversations and collaborations that shaped this work. I would like to especially thank Sophia B. Liu, Sarah Vieweg and Amanda Hughes, whose research set the foundations for mine, and who supported me throughout my PhD studies with conversation, ideas, edits, and inspiration. I’d also like to thank peers that arrived on the scene later, especially Joanne White, who both supported my research and helped guide the development of my many projects. Certainly, the Tweak the Tweet project would never have gotten off the ground without the many hundreds and possibly thousands of tweets sent by Sophia, Sarah, Amanda and Jo. I also cannot thank enough the other side of Project EPIC, those building the systems to support our research and staying up late at night and sometimes all night to keep those systems running. Specifically, I am grateful for the herculean efforts of Ken Anderson and Aaron Schram to collect something approaching terabytes of Twitter data to support my research, and for their Zen-like ability to weather the franticness of my collection requests which, unfortunately for the two of them, were tuned into the rhythms of disaster—rhythms that do not align at all with the natural rhythms of human life. I would also like to acknowledge my colleagues at the ATLAS Institute, including my fellow students who contributed to my academic development, the staff who helped me over all the administrative hurdles in a PhD career, and the two Directors of ATLAS, John Bennett and Bobby v Schnabel, for their support. Though Bobby left CU and ATLAS before my first class as a PhD student, I am extremely grateful for his oh-so-slight intervention in my life 6 years ago, when he urged me to apply to ATLAS and then eventually convinced me to enroll. I am also grateful to him for continuing to mentor me from afar, and making time for me whenever he returned to Boulder. There is one more person without whom I would not have completed this work – or even started it. Thank you, Melissa, my partner/wife, for holding my hand through my transition from my first career to my second one, for helping me decide that ATLAS was the place for me, and for sticking with me in Boulder even though you were too allergic to go outside there from April to October. When I became a hermit in my back office, tweeting, I mean, writing away, you continued to bring food to my door (and to tell me to get back to work when I was fading). Thank you! Finally, here, I would like to thank the dozens and possibly hundreds of digital volunteers with whom I have come in contact over the last few years. Thank you for all the work you do for people in need all over the world! And thank you for supporting Tweak the Tweet and for tolerating my constant inquiries into how and why you do the things you do. Special thanks go to the many volunteers at Humanity Road. Financial support for this work was provided through a National Science Foundation Graduate Fellowship and NSF grants #IIS-0546315 and #IIS-0910586. vi TABLE OF CONTENTS Acknowledgments..........................................................................................................................v Table of Contents.........................................................................................................................vii CHAPTER 1 Introduction: Mass Disruption and Information Convergence ........................1 1.1 Converging through Social Media ..................................................................................1 1.2 The “Problem” of Informational Convergence .............................................................3 1.3 The Work of Information Processing during Mass Disruption...................................6 1.4 Crowdwork .......................................................................................................................8 1.5 Structure of the Dissertation .........................................................................................10 1.5.1 Integration of Previously Published Work ................................................................11 CHAPTER 2 Background: Social Media, Mass Disruption and Crowd Work ....................12 2.1 Social Media....................................................................................................................13

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