Big Data on Human and Social Sciences – History, Issues and Challenges
Humanists and social scientists have at their disposal an unprecedented amount of data today. For sure, the wide variety of data available, including the massively growing public archival data, creates many opportunities. For instance, it allows to extend the geographical and longitudinal scope of analysis on a new scale. But nor the data existent in social and historical processes is neutral nor the ways to store, retrieve and analyse such amount of data is based upon simplistic decisions.
With their capacity to historically situate the objects of analysis, discuss meanings and vast textual corpora, as well as their strength on contextual knowledge, historians, sociologists, political scientists, economists, philosophers and anthropologists are in strong position to contribute to this revolution. Grounded on the presence of academic experts from such fields of knowledge, this Congress will cover a wide range of topics aiming to build bridges with formal, applied and natural scientists and to open windows into the public domain.
What can we learn from the rise and fall of cliometrics, and how will humanists receive new research using computational methods? What are the biggest challenges, opportunities, and pitfalls in applying computational methods to historical data? If these new methods actually lead to new discoveries, will that change standards of evidence, and challenge claims based on purely qualitative research?
We welcome proposals for individual papers to address these but also other questions. Some of the topics include but are not limited to:
– History of Big Data;
– Big data and modes of knowledge production;
– Big data. Pitfalls and errors;
– Development of complex datasets;
– Big Data and networks;
– Digital Humanities and historical research;
– Archives, libraries and Big Data;
– Historical Big Data and statistical tools;
– Text mining and historical sources;
– Big data management for researchers and research institutions;
– Big data infrastructures.
Keynote Speakers (confirmed): Matthew Connelly (Columbia University)
For more information please click "Further Official Information" below.