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Identifying, Organizing, and Presenting Correlations Between Social Media and Broadcast Television

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Identifying, Organizing, and Presenting Correlations Between Social Media and Broadcast Television The Revolution Will Be Televised: Identifying, Organizing, and Presenting Correlations Between Social Media and Broadcast Television By Patrick Florence Riley A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Information Management and Systems in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Yale Braunstein, Chair Professor Emeritus Todd LaPorte Professor John Chuang Fall 2011 The Revolution Will Be Televised: Identifying, Organizing, and Presenting Correlations Between Social Media and Broadcast Television © 2011, All Rights Reserved Patrick Florence Riley Abstract The Revolution Will Be Televised: Identifying, Organizing, and Presenting Correlations Between Social Media and Broadcast Television by Patrick Florence Riley Doctor of Philosophy in Information Management and Systems University of California, Berkeley Professor Yale Braunstein, Chair Many popular facets of live information, known collectively as communication technology, deliver ongoing, socially-relevant narrations of our world. Traditionally, different types of communication media were considered to be in competition, but recently they have been discovered to be complementary and synergistic. This paper will concentrate on the role, influence, and potential of the integration of various types of communication media with particular attention to the recent phenomenon of social media and broadcast television. This research demonstrates how to develop a listening platform that enables one to capture, parse, analyze, cluster and present correlations between social media and broadcast television. The listening platform, called LiveDash for this research, uses a number of innovative media real-time media capturing, link analysis, clustering, and social networking analysis techniques to provide an immediate “system of record” of what is being mentioned on television, social networks, and journalism wires. Using media servers designed specifically for this project, LiveDash captures and records all national television channels from the United States, and incrementally indexes what is said on Broadcast Television in real-time. LiveDash also crawls the links people share on Twitter, Digg, and other social sharing services, and indexes the content on those pages as soon as they are shared, allowing users to find the newest, most socially-relevant content in real-time. Due to this sophisticated system, it is now possible to identify and comprehend the correlations of information between social media and broadcast television. Moreover, by conducting annual surveys and user experience research, this research explores the simultaneous usage of social media and broadcast television by users. With over two million unique visits to Livedash.com last year alone, this research demonstrates that not only are users increasingly using social media and broadcast television simultaneously, but also value interactivity and contextual, correlated information to augment their broadcast television experience. LiveDash and its mobile device component, LiveDash Mobile, show how users react, process, and value additional computer recommended social media while watching broadcast television. A REST API for the LiveDash system has also been made available for academic uses and further research. 1 Dedication I dedicate this dissertation to my close friends and family, especially… to Yale for his dedication, friendship and lessons of diplomacy; to Laurie for opening my eyes to the opportunities of this world; to Charles for instilling the importance of hard work and sacrifice; to Amy—may you be motivated and inspired to reach your dreams; and to Del and John, who have since past but will never be forgotten. i Contents List of Tables and Figures . v Acknowledgements . vi 1 Introduction 1 1.1 Correlations between Social and Broadcast Media . 1 1.1.1 JetBlue . 2 1.1.2 Hudson River Plane Crash . 4 1.1.3 Curling at the 2010 Winter Olympics . 6 1.1.4 Oxygen Live and Bad Girls Club . 7 1.1.5 ABC Academy Awards . 8 1.1.6 Viewing Howard Stern’s Private Parts . 9 1.2 The Evolution Towards an Interactive Three Screen Experience . 11 1.3 Dissertation Focus and Purpose . 13 2 Background and Previous Contributions 14 2.1 Classical Informational Search and Retrieval Literature . 14 2.2 Search Engine Priority Scores, Ranking Algorithms and Sensitivities . 16 2.3 Determining Influence, Credibility and Authority . 18 2.4 Information Interfaces and Presentation . 20 2.5 Clustering and Link Analysis . 22 2.6 Media Segmentation and Classification . 24 ii 3 Information System and Research 27 3.1 The Anatomy of a Social and Broadcast Media Listening Platform . 27 3.1.1 Correlating Broadcast Television and Social Media . 27 3.1.2 The Challenges of Data Mining the Internet . 27 3.1.3 Mining for Co-occurrences and Association Rules . 29 3.1.4 Mining Class Association Rules . 33 3.1.5 Mining for Sequential Patterns: GSP and PrefixSpan . 34 3.1.6 Supervised Learning . 36 3.1.7 Classifier Evaluation . 40 3.1.8 Rule Induction . 41 3.1.9 Classifications Based on Associations . 42 3.1.10 Capturing Broadcast Television Media . 47 3.2 Clustering, Analysis and Correlations between Social and Broadcast Media . 48 3.2.1 Overview . 48 3.2.2 Gathering Information on Broadcast Media . 49 3.2.3 Segmentation of Data: Classification and Clustering . 52 3.2.4 Correlations: Temporal, Geographical, and Semantic . 57 3.2.5 Semantic Correlations, Indexing, and Link Analysis . 59 3.2.6 Evaluation . 65 3.3 Information Consumption and Needs of Users . 65 3.3.1 Motivation and Concurrent Behavior . 68 3.3.2 The Roles of Social and Broadcast Television Media . 68 iii 3.4 Information Interface and Presentation User Research . 72 4 Conclusion 81 4.1 Contributions . 81 4.2 Suggestions for Future Research . 83 Bibliography Appendices A 1.1 Live TV API A 1.2 Shared Links API A 1.3 Video API A 1.4 News API A 1.5 Blogs API A 1.6 Forums API iv List of Tables and Figures Figure 1. Photograph by Janis Krums of the Hudson River Plane Crash Figure 2. Tweet by Janis Krums describing Hudson River Plane Crash Figure 3. Information Technology Environment of the LiveDash System Figure 4. LiveDash Broadcast Television Capture Flow Figure 5. Screen capture of the LiveDash executing the search query “blackberry” with the Shared Links search filter Figure 6. Screen capture of the LiveDash executing the search query “Nikon d90” with the Shared Links search filter Figure 7. Results of livedash.com visitor survey across three years Figure 8. Concurrent Use of TV & Internet is Becoming Mainstream Figure 9. Both TV and Online Advertising Can Fulfill Roles Across All Stages Figure 10. Using Both TV & Online Brings the Audience Closer to the Brand Figure 11. Livedash.com Public Web Traffic. Figure 12. Screen capture of LiveDash Mobile on an Apple I-Pod Touch Figure 13. Screen shot of a search executed on Livedash.com for the query “all you can fly” v Acknowledgements As both an undergraduate and graduate student at the University of California, Berkeley, I have had the distinct privilege to work with so many of you talented and dedicated individuals. I would like to express my sincere gratitude to Professor Yale Braunstein for his guidance, diplomacy, patience, and most importantly, his friendship during my graduate career. His mentorship was essential in encouraging me to not only grow as a scholar and an entrepreneur, but also as a leader and an independent thinker overall. Ever since my first graduate course with Professor John Chuang, Distributed Computer Applications, I have been both extremely intimidated and yet, thankful for both his expertise in Computer Science, but also the Economics that are embedded in this field. Despite his impacted schedule, John always finds the time to discuss anything—from how to most securely write a networked application, to the underlying economic motivations to why people use technology a certain way. These two friends and colleagues are overwhelming responsible for my deep loyalty and appreciate to the University of California, Berkeley's School of Information. Interestingly enough, I am certain I would not have discovered the School of Information had it not been for Professor Todd LaPorte, from the Department of Political Science at Berkeley. Having been inspired from his undergraduate courses and reading his influential technology policy papers, Todd's interest, support, and encouragement over the last ten years of my Berkeley career has lead me to where I am today. Todd, your unique prospective on technology kept me determined to find the larger vision, and build a system that all fields of academics and industry can use. I’d also like to thank Professor Ray Larson for not only teaching me the fundamentals of information retrieval, but also for inspiring me to contribute back to this increasingly important field in a meaningful way. I should also thank Professor Pamela Samuelson, who first introduced me, and suggested I should apply to the School of Information while we were both colleagues at the Law School. I would also like to thank the entire School of Information community and employees who contributed their knowledge, support, and accessibility. In particular, I would like to thank Roberta Epstein, Lety Sanchez, Meg St. John and Kevin Heard, for their dedication and unwavering support. Finally, and most importantly, I would like to thank my entire family, those still remaining, and those who have passed on, for their endless understanding, support, and inspiration. Thank you all for your contributions. I can only hope to someday earn all that you have sacrificed with a career of purpose and efficacy. vi Chapter 1 Introduction 1.1 Correlations Between Social and Broadcast Media Traditionally, social and broadcast media have been viewed as separate and even opposing entities.1 It was thought that as more people began using the Web in their spare time, fewer of them were watching television. Along with increasingly sophisticated recording technology that allows viewers to watch television whenever they want, the Internet and technological advances threatened television‟s claim to a captive audience.
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