Roles, trust, and reputation in social media knowledge markets (book)

The first major publication of the KredibleNet project is out. The volume  Roles, Trust, and Reputation in Social Media Knowledge Markets: Theory and Methods discusses the emerging trends in defining, measuring, and operationalizing reputation as a new and essential component of the knowledge that is generated and consumed online. The book also proposes a future research agenda related to these issues—with the ultimate goal of shaping the next generation of theoretical and analytic strategies needed for understanding how knowledge markets are influenced by social interactions and reputations built around functional roles.

Roles, Trust, and Reputation in Social Media Knowledge Markets exposes issues that have not been satisfactorily dealt with in the current literature. In a broader sense, the volume aims to change the way in which knowledge generation in social media spaces is understood and utilized. The tools, theories, and methodologies proposed here offer concrete avenues for developing the next generation of research strategies and applications that will help: tomorrow’s information consumers make smarter choices, developers to create new tools, and researchers to launch new research programs.

 

Contents

Part I Introduction

A Research Agenda for the Study of Entropic Social Structural Evolution, Functional Roles, Adhocratic Leadership Styles, and Credibility in Online Organizations and Knowledge Markets

Sorin Adam Matei, Elisa Bertino, Michael Zhu, Chuanhai Liu, Luo Si and Brian Britt

Building Trusted Social Media Communities: A Research Roadmap for Promoting Credible Content

Ben Shneiderman

Part II Methods for Researching Trust and Credibility

Semantic and Social Spaces: Identifying Keyword Similarity with Relations

Yun Huang, CindyWeng, Baozhen Lee and Noshir Contractor

Emergent Social Roles in Wikipedia’s Breaking News Collaborations

Brian C. Keegan

Words and Networks: How Reliable Are Network Data Constructed from Text Data?

Jana Diesner

Predicting Low-Quality Wikipedia Articles Using User’s Judgements

Ning Zhang, Lingyun Ruan and Luo Si

Part III Tools for Enhancing Trust and Transparency

From Invisible Algorithms to Interactive Affordances: Data After the Ideology of Machine Learning

Bernie Hogan

Part IV Novel Research Directions

Breaking the Iron Law of Oligarchy: Computational Institutions, Organizational Fidelity, and Distributed Social Control

Howard T.Welser

Cultural Differences in Social Media: Trust and Authority

Mei Kobayashi

Convincing Evidence

Andrew Gelman and Keith O’Rourke

Part V Research Opportunities and Gaps in Trust, Credibility, and Authorship Research

The Trajectory of Current and Future Knowledge Market Research: Insights from the First KredibleNet Workshop

Sorin Adam Matei, Brian Britt, Elisa Bertino and Jeremy Foote

Sorin Adam Matei

Sorin Adam Matei – Professor of Communication at Purdue University – studies the relationship between information technology and social groups. He published papers and articles in Journal of Communication, Communication Research, Information Society, and Foreign Policy. He is the author or co-editor of several books. The most recent is Structural differentation in social media. He also co-edited Ethical Reasoning in Big Data,Transparency in social media and Roles, Trust, and Reputation in Social Media Knowledge Markets: Theory and Methods (Computational Social Sciences) , all three the product of the NSF funded KredibleNet project. Dr. Matei’s teaching portfolio includes online interaction, and online community analytics and development classes. His teaching makes use of a number of software platforms he has codeveloped, such as Visible Effort . Dr. Matei is also known for his media work. He is a former BBC World Service journalist whose contributions have been published in Esquire and several leading Romanian newspapers. In Romania, he is known for his books Boierii Mintii (The Mind Boyars), Idolii forului (Idols of the forum), and Idei de schimb (Spare ideas).

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