Speaking Sociologically with Big Data: Symphonic Social Science and the Future for Big Data Research

Recent years have seen persistent tension between proponents of big data analytics, using new forms of digital data to make computational and statistical claims about ‘the social’, and many sociologists sceptical about the value of big data, its associated methods and claims to knowledge. We seek to move beyond this, taking inspiration from a mode of argumentation pursued by Piketty, Putnam and Wilkinson and Pickett that we label ‘symphonic social science’. This bears both striking similarities and significant differences to the big data paradigm and – as such – offers the potential to do big data analytics differently. This offers value to those already working with big data – for whom the difficulties of making useful and sustainable claims about the social are increasingly apparent – and to sociologists, offering a mode of practice that might shape big data analytics for the future.

[1]  P. Bourdieu.  Distinction: A Social Critique of the Judgement of Taste* , 2018, Food and Culture.

[2]  Arie Rip,et al.  Knowledge and society : studies in the sociology of culture past and present : a research annual , 1981 .

[3]  Edward Rolf Tufte,et al.  The visual display of quantitative information , 1985 .

[4]  E. Tufte,et al.  The visual display of quantitative information , 1984, The SAGE Encyclopedia of Research Design.

[5]  P. Fayers,et al.  The Visual Display of Quantitative Information , 1990 .

[6]  John Scott.  Social Network Analysis , 1988 .

[7]  J. Goldthorpe,et al.  The Constant Flux: A Study of Class Mobility in Industrial Societies , 1993 .

[8]  Bethany Bryson,et al.  Anything but heavy metal : Symbolic exclusion and musical dislikes , 1996 .

[9]  R. Inglehart.  Modernization and Postmodernization: Cultural, Economic, and Political Change in 43 Societies , 1997 .

[10]  M. Hout,et al.  Modernization and Postmodernization: Cultural, Economic, and Political Change in Forty-three Societies , 1998 .

[11]  Robert D. Putnam,et al.  Bowling alone: the collapse and revival of American community , 2000, CSCW '00.

[12]  W. Galston.  Bowling Alone: The Collapse and Revival of American Community , 2001 .

[13]  M. Gluck,et al.  The Flâneur and the Aesthetic , 2003 .

[14]  Paul DiMaggio,et al.  Arts participation as cultural capital in the United States, 1982–2002: Signs of decline? , 2004 .

[15]  Richard Lloyd,et al.  The Neighborhood in Cultural Production: Material and Symbolic Resources in the New Bohemia , 2004 .

[16]  R. Burt.  Brokerage and Closure: An Introduction to Social Capital , 2005 .

[17]  Oriel Sullivan,et al.  The omnivore thesis revisited: Voracious cultural consumers , 2006 .

[18]  Tom Slater,et al.  The Eviction of Critical Perspectives from Gentrification Research , 2006 .

[19]  Roger Burrows,et al.  The Coming Crisis of Empirical Sociology , 2007, Sociology.

[20]  Matthew Fuller,et al.  Software Studies: a lexicon , 2008 .

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

[22]  Rosemary Crompton,et al.  Forty Years of Sociology , 2008 .

[23]  G. Bellavance.  Where's high? Who's low? What's new? Classification and stratification inside cultural “Repertoires” , 2008 .

[24]  Roger Burrows,et al.  Some Further Reflections on the Coming Crisis of Empirical Sociology , 2009 .

[25]  R. Webber.  Response to `The Coming Crisis of Empirical Sociology': An Outline of the Research Potential of Administrative and Transactional Data , 2009 .

[26]  J. Goldthorpe.  Analysing Social Inequality: A Critique of Two Recent Contributions from Economics and Epidemiology , 2010 .

[27]  R. Wilkinson,et al.  The spirit level : why equality is better for everyone , 2010 .

[28]  D. M. Berry,et al.  The Philosophy of Software , 2011 .

[29]  Rob Kitchin,et al.  Code/Space: Software and Everyday Life , 2011 .

[30]  M. Savage,et al.  The Double Social Life of Methods , 2011 .

[31]  D. Boyd,et al.  Six Provocations for Big Data , 2011 .

[32]  Duncan J. Watts,et al.  Everything is obvious : how common sense fails , 2011 .

[33]  M. Wettler.  The Spirit Level: Why Equality Is Better for Everyone , 2011 .

[34]  Mark Andrejevic,et al.  THE WORK THAT AFFECTIVE ECONOMICS DOES , 2011 .

[35]  L. Manovich,et al.  Trending: The Promises and the Challenges of Big Social Data , 2012 .

[36]  Etude approfondie des pratiques et consommation culturelles de la population en Fédération Wallonie-Bruxelles: Les publics de la culture , 2012 .

[37]  Bruno Latour,et al.  Visualisation and Cognition: Drawing Things Together , 2012 .

[38]  M. Savage,et al.  Elaborating Bourdieu's Field Analysis in Urban Studies: Cultural Dynamics in Brussels , 2012 .

[39]  H. Kennedy.  Perspectives on Sentiment Analysis , 2012 .

[40]  Mike Savage,et al.  The ‘Social Life of Methods’: A Critical Introduction , 2013 .

[41]  Laurie Hanquinet.  Visitors to Modern and Contemporary Art Museums: Towards a New Sociology of ‘Cultural Profiles’ , 2013 .

[42]  Viktor Mayer-Schnberger,et al.  Big Data: A Revolution That Will Transform How We Live, Work, and Think , 2013 .

[43]  N. Marres,et al.  SCRAPING THE SOCIAL? , 2013 .

[44]  T. Piketty.  Capital in the twenty-first century: a multidimensional approach to the history of capital and social classes. , 2013, The British journal of sociology.

[45]  Mark J. Weal,et al.  Digital Futures? Sociological Challenges and Opportunities in the Emergent Semantic Web , 2013 .

[46]  Rachel Schutt,et al.  Doing Data Science , 2013 .

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

[48]  M. Savage,et al.  The Eyes of the Beholder: Aesthetic Preferences and the Remaking of Cultural Capital , 2014 .

[49]  Robert W. Gehl,et al.  Critical Reverse Engineering: The Case of Twitter and Talkopen , 2014 .

[50]  S. Halford,et al.  Big Data: Methodological Challenges and Approaches for Sociological Analysis , 2014 .

[51]  Kevin Driscoll,et al.  Big Data, Big Questions| Working Within a Black Box: Transparency in the Collection and Production of Big Twitter Data , 2014 .

[52]  Kate M. Miltner,et al.  Critiquing Big Data: Politics, Ethics, Epistemology , 2014 .

[53]  James Moody,et al.  Data Visualization in Sociology. , 2014, Annual review of sociology.

[54]  Rob Kitchin,et al.  The data revolution : big data, open data, data infrastructures & their consequences , 2014 .

[55]  R. Kitchin,et al.  Big Data, new epistemologies and paradigm shifts , 2014, Big Data Soc..

[56]  M. Savage.  Piketty's challenge for sociology. , 2014, The British journal of sociology.

[57]  Michael W. Macy,et al.  The paradox of active users , 2015 .

[58]  Daniel A. McFarland,et al.  Big Data and the danger of being precisely inaccurate , 2015, Big Data Soc..

[59]  Surfeit and surface , 2015 .

[60]  Ronald L. Breiger,et al.  Ontologies, methodologies, and new uses of Big Data in the social and cultural sciences , 2015 .

[61]  Olha Buchel,et al.  Big Data: A Revolution That Will Transform How We Live, Work, and Think , 2015 .

[62]  Axel Bruns,et al.  Compromised Data: From Social Media to Big Data , 2015 .

[63]  Shoshana Zuboff,et al.  Big other: surveillance capitalism and the prospects of an information civilization , 2015, J. Inf. Technol..

[64]  R. Buurma.  The fictionality of topic modeling: Machine reading Anthony Trollope's Barsetshire series , 2015 .

[65]  Kevin Lewis,et al.  Three fallacies of digital footprints , 2015, Big Data Soc..

[66]  J. Goldthorpe.  Sociology as a Population Science , 2015 .

[67]  N. Marres.  Interface Methods Renegotiating relations between digital social research , STS and the sociology of innovation , 2015 .

[68]  Will Jennings,et al.  Small Big Data: Using multiple data-sets to explore unfolding social and economic change , 2015, Big Data Soc..

[69]  Ted Underwood,et al.  The literary uses of high-dimensional space , 2015 .

[70]  M. Savage,et al.  Social Class in the 21st Century , 2015 .

[71]  Eric Gossett,et al.  Big Data: A Revolution That Will Transform How We Live, Work, and Think , 2015 .

[72]  Ryan Shaw.  Big Data and reality , 2015 .

[73]  David M. Rothschild,et al.  Forecasting elections with non-representative polls , 2015 .

[74]  N. Couldry.  Researching social analytics: cultural sociology in the face of algorithmic power , 2015 .

[75]  Amir Goldberg.  In defense of forensic social science , 2015 .

[76]  Paul DiMaggio,et al.  Adapting computational text analysis to social science (and vice versa) , 2015, Big Data Soc..

[77]  Ben Shneiderman,et al.  The New ABCs of Research: Achieving Breakthrough Collaborations , 2016 .

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

[79]  Joseph Y. S. Cheng,et al.  Capital in the Twenty-First Century , 2016 .

[80]  C. Frade.  Social Theory and the Politics of Big Data and Method , 2016 .

[81]  C. Bail.  Emotional Feedback and the Viral Spread of Social Media Messages About Autism Spectrum Disorders. , 2016, American journal of public health.

[82]  Carolin Gerlitz,et al.  Interface Methods: Renegotiating Relations between Digital Social Research, STS and Sociology , 2016 .

[83]  M. Williams,et al.  Crime sensing with big data: the affordances and limitations of using open source communications to estimate crime patterns , 2016 .

[84]  Barbara Martini,et al.  The Data Revolution. Big Data, Open Data, Data Infrastructures and Their Consequences , 2016 .