Abstract
This chapter presents a summary of the themes, topics, methods and case studies presented at the Kredible.net workshop on Reputation, Trust and Authority, held at Stanford University in 2013. The workshop brought together scholars from a variety of disciplines to explore how—amidst the Internet’s enormous volume of content and relationships—certain topics, concepts and individuals rise to prominence, develop strong reputations, gain followers and establish credibility and trust. The projects presented in this paper explore the emergence of social roles, the creation of value, and the perception of credibility and trustworthiness in online information. They combine social science insights into the structure and nature of online interaction with advances in computational science, data visualization, graph analysis and natural language processing. The methods and results presented in this paper offer innovative statistical strategies, models, and methodologies for navigating the large and complex data sets produced by online content.
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PI: Sorin Adam Matei, CoPIs: Elisa Bertino, Michael Zhu, Chuanhai Liu
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Martha Russell, Executive Director
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Marc Smith
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Suddenly Social, CEO
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Edelman, Senior Vice President
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Google
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Purdue University
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Purdue University
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University of Ohio
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Stanford University
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University of Illinois
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Purdue University
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University of Georgia
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University of Washington
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Stanford University
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VTT, Finland
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Tempere University of Technology
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Infobitt
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Stanford University
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Purdue University
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Texas A&M University
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University of Ohio, “Breaking the Iron Law of Oligarchy: Computational Institutions, Reputation Systems and Distributed Social Control”
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Stanford University, “Steering User Behavior with Badges”
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University of Illinois, “How do Social Roles, Reputation and Authority Emerge on Social-media Knowledge-generation Projects”
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Purdue University, “A Learning Approach for Web Social Emotion Detection”
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University of Georgia, “The Affordable Care Act on Twitter”
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Stanford University, “How Social Media Reflect Decisions and Outcomes in the Physical World”
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University of Washington, “Social Media and Protest”
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Stanford University, “Understanding the Wealth-Creating Potential of Relationships Beyond Pretty Pictures Based on the ‘Fluff’ of Social Media”
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VTT Technical Research Center, “Understanding the Wealth-Creating Potential of Relationships Beyond Pretty Pictures Based on the ‘Fluff’ of Social Media”
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Tampere University of Technology, “Data-Driven Network Analytics in the Cloud”
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Infobitt, “How to Crowdsource a High-Quality News Site”
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Stanford University, “Enabling Expert Crowdsourcing with Flash Teams”
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Purdue University, “Mythbusting in Research and Educational Networks”
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Texas A&M University, “Detecting and Preventing Crowdsourced Manipulation of Social Media and Online Communities”
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Alexanyan, K., Matei, S.A., Russell, M. (2015). Socio-Computational Frameworks, Tools and Algorithms for Supporting Transparent Authorship in Social Media Knowledge Markets. In: Matei, S., Russell, M., Bertino, E. (eds) Transparency in Social Media. Computational Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-18552-1_2
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DOI: https://doi.org/10.1007/978-3-319-18552-1_2
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