Big Data in Public Affairs

This article offers an overview of the conceptual, substantive, and practical issues surrounding “big data” to provide one perspective on how the field of public affairs can successfully cope with the big data revolution. Big data in public affairs refers to a combination of administrative data collected through traditional means and large-scale data sets created by sensors, computer networks, or individuals as they use the Internet. In public affairs, new opportunities for real-time insights into behavioral patterns are emerging but are bound by safeguards limiting government reach through the restriction of the collection and analysis of these data. To address both the opportunities and challenges of this emerging phenomenon, the authors first review the evolving canon of big data articles across related fields. Second, they derive a working definition of big data in public affairs. Third, they review the methodological and analytic challenges of using big data in public affairs scholarship and practice. The article concludes with implications for public affairs.

[1]  C. Hoffmann,et al.  Towards a Broader Understanding of the Participation Divide(s) , 2014 .

[2]  M. Moore Creating public value : strategic management in government , 1995 .

[3]  A-L Barabási,et al.  Structure and tie strengths in mobile communication networks , 2006, Proceedings of the National Academy of Sciences.

[4]  Rob Kitchin,et al.  What makes Big Data, Big Data? Exploring the ontological characteristics of 26 datasets , 2016, Big Data Soc..

[5]  Veda C. Storey,et al.  Business Intelligence and Analytics: From Big Data to Big Impact , 2012, MIS Q..

[6]  Alex Pentland,et al.  Big Data and Management , 2014 .

[7]  Charles Anderson,et al.  The end of theory: The data deluge makes the scientific method obsolete , 2008 .

[8]  J. Manyika Big data: The next frontier for innovation, competition, and productivity , 2011 .

[9]  Erik Johnston,et al.  Governance in the information era : theory and practice of policy informatics , 2015 .

[10]  H. Varian,et al.  Predicting the Present with Google Trends , 2012 .

[11]  R. Behn The Big Questions of Public Management , 1995 .

[12]  Alessandro Acquisti,et al.  Predicting Social Security numbers from public data , 2009, Proceedings of the National Academy of Sciences.

[13]  Cory Doctorow Big data: Welcome to the petacentre , 2008, Nature.

[14]  D. Moynihan Why and How Do State Governments Adopt and Implement “Managing for Results” Reforms? , 2004 .

[15]  Teresa Correa,et al.  The Participation Divide Among "Online Experts": Experience, Skills and Psychological Factors as Predictors of College Students' Web Content Creation , 2010, J. Comput. Mediat. Commun..

[16]  M. Pirog DATA WILL DRIVE INNOVATION IN PUBLIC POLICY AND MANAGEMENT RESEARCH IN THE NEXT DECADE , 2014 .

[17]  Bradley E. Wright,et al.  Motivated to Adapt? The Role of Public Service Motivation as Employees Face Organizational Change , 2013 .

[18]  Lisa A Bero,et al.  "Developing good taste in evidence": facilitators of and hindrances to evidence-informed health policymaking in state government. , 2008, The Milbank quarterly.

[19]  Matt Golder,et al.  Big Data, Causal Inference, and Formal Theory: Contradictory Trends in Political Science? , 2014, PS: Political Science & Politics.

[20]  D. Boyd,et al.  CRITICAL QUESTIONS FOR BIG DATA , 2012 .

[21]  Eszter Hargittai,et al.  Second-Level Digital Divide: Differences in People's Online Skills , 2002, First Monday.

[22]  J. Schradie The Gendered Digital Production Gap: Inequalities of Affluence , 2015 .

[23]  J. Schradie The digital production gap: The digital divide and Web 2.0 collide , 2011 .

[24]  C. Lynch Big data: How do your data grow? , 2008, Nature.

[25]  A. Pentland,et al.  Computational Social Science , 2009, Science.

[26]  John J. Kirlin The Big Questions of Public Administration in a Democracy , 1996 .

[27]  Kimberley R. Isett,et al.  Caveat Emptor: What Do We Know about Public Administration Evidence and How Do We Know It? , 2016 .

[28]  Marijn Janssen,et al.  Big and Open Linked Data (BOLD) in government: A challenge to transparency and privacy? , 2015, Gov. Inf. Q..

[29]  Felice C. Frankel,et al.  Big data: Distilling meaning from data , 2008, Nature.

[30]  Mark H. Moore,et al.  Public Value Accounting: Establishing the Philosophical Basis , 2014 .

[31]  E. Gerrish The Impact of Performance Management on Performance in Public Organizations: A Meta-Analysis , 2014 .

[32]  Stéphane Lavertu,et al.  We All Need Help: “Big Data” and the Mismeasure of Public Administration , 2016 .

[33]  H. Varian,et al.  Predicting the Present with Google Trends , 2009 .

[34]  K. Meier,et al.  Managerial Networking , 2005 .

[35]  D. Lazer,et al.  The Parable of Google Flu: Traps in Big Data Analysis , 2014, Science.

[36]  Manuel Cebrián,et al.  Social Media Fingerprints of Unemployment , 2014, PloS one.

[37]  John M. Bryson,et al.  Public value governance: Moving beyond traditional public administration and the new public management , 2014 .

[38]  John P. Robinson,et al.  Social Implications of the Internet , 2001 .

[39]  D. Moynihan,et al.  Look for the Silver Lining: When Performance‐Based Accountability Systems Work , 2003 .

[40]  R. Brownson,et al.  Evidence-based public health: a fundamental concept for public health practice. , 2009, Annual review of public health.

[41]  David Lazer,et al.  Inferring friendship network structure by using mobile phone data , 2009, Proceedings of the National Academy of Sciences.

[42]  Claudio Cioffi-Revilla,et al.  Computational social science , 2010 .