2016 Workshop 6 – Social Set Analysis: A Set-Theoretical Approach to Computational Social Science

Abstract: This tutorial proposes and demonstrates a new holistic approach to computational social science in general and big social data analytics in particular based on the social philosophy of associations, mathematics of set theory and the methods of social set analysis. The set theoretical approach addresses current theoretical challenges and methodological limitations in computational social science in general and big social data analytics in particular about social structure vs. individual agency, social order vs. complexity, common method bias, and endogeneity. This tutorial will contain both “show-and-tell” demos and “hands-on” training for formally modelling massive volumes of big social data constituting individual human online interactions as unordered sets with ideas, values, objects, artefacts, and social others and conducting event studies of a social media crises dataset from Facebook.

Pre-Workshop Prep:
No Prerequisites Required

Workshop Contacts
Ravi Vatrapu – vatrapu@cbs.dk
Raghava Rao Mukkamala – rrm.itm@cbs.dk 

Presenter Bios:

bm0108_nr3_ravi_vatrapu_5405Ravi Vatrapu is a professor of human computer interaction at the Department of IT Management, Copenhagen Business School; professor of applied computing at the Westerdals Oslo School of Arts Communication and Technology; and director of the Computational Social Science Laboratory (http://cssl.cbs.dk). Prof. Vatrapu’s current research focus is on big social data analytics. Based on the enactive approach to the philosophy of mind and phenomenological approach to sociology and the mathematics of classical, fuzzy and rough set theories, his current research program seeks to design, develop and evaluate a new holistic approach to computational social science, Social Set Analytics (SSA). SSA consists of novel formal models, predictive methods and visual analytics tools for big social data. Prof. Vatrapu holds a Doctor of Philosophy (PhD) degree in Communication and Information Sciences from the University of Hawaii at Manoa, a Master of Science (M.Sc) in Computer Science and Applications from Virginia Tech, and a Bachelor of Technology in Computer Science and Systems Engineering from Andhra University. He can be reached at vatrapu@cbs.dk.

RaoPassportRaghava Mukkamala is an assistant professor of Computational Social Science at the Department of IT Management, Copenhagen Business School; external lecturer of applied computing at the Westerdals Oslo School of Arts Communication and Technology; and co-director of the Computational Social Science Laboratory (http://cssl.cbs.dk). Raghava’s current research focus is on interdisciplinary approach to big data analytics. Combining formal/mathematical modeling approaches with data/text mining techniques and machine learning methodologies, his current research program seeks to develop new algorithms and techniques for big data analytics such as Social Set Analytics. Raghava holds a PhD degree in Computer Science and a M.Sc degree in Information Technology, both from IT University of Copenhagen, Denmark and a Bachelor of Technology degree from Jawaharlal Nehru Technological University, India. Before moving to research, Raghava has many of years of programming and IT development experience from Danish IT industry. He can be reached at rrm.itm@cbs.dk.

abid_hussain_cropped_322Abid Hussain is an assistant professor of Computational Social Science at the Department of IT Management, Copenhagen Business School and Associate Researcher at the Computational Social Science Laboratory (http://cssl.cbs.dk). Abid’s research focus is on the design, development and evaluation of design principles and design patterns for the systematic collection, storage, retrieval and processing of big social data. He is the lead researcher and developer of the Social Data Analytics Tool (www.sodato.net), the first research-based big social data analytics tool for Facebook. He has more than ten years of software development experience in the IT industry where he has served as the system architect and lead developer on software teams ranging upto 40 members. He holds a Master of Science in Software Development from the IT University of Copenhagen, Denmark; a Graduate Diploma in Information Systems Management from the Central Queensland University, Australia; and a Diploma in Information Technology and Software Development from Holmesglen Institute, Australia. He can be reached at ah.itm@cbs.dk.

niels_li.jpgNiels Buus Lassen is a PhD Fellow of Computational Social Science at the Department of IT Management, Copenhagen Business School and research fellow at the Computational Social Science Laboratory (http://cssl.cbs.dk). His research interests are in modelling big social data in order to build and validate predictive models of real-world phenomena such as sales, revenues, stock prices, brand parameters and public health parameters. He holds a MSc in Economics and BSc in Economics & Mathematics from Copenhagen Business School, and a MBA from Edinburgh Business School. He can be reached at nbl.itm@cbs.dk.

Benjamin Flesch is a PhD Fellow of Computational Social Science at the Department of IT Management, Copenhagen Business School and research fellow at the Computational Social Science Laboratory (http://cssl.cbs.dk). His research aims to formulate and evaluate a new field of study, “Computational Set Analysis” in general and Computational Set Visualisations in particular. His PhD project aims to design, develop and evaluate Social Set Visualiser (SoSeVi) based on set-theoretical approach to computational social science. He holds a Master of Science in Business Administration and Information Systems from Copenhagen Business School, Denmark and Master of Science in Business Administration from University of Mannheim, Germany. He can be reached at bf.itm@cbs.dk.

Comments are closed.