Center for Business Data Analytics(cbsBDA) at the Department of Digitalization of the Copenhagen Business School conducts transdisciplinary basic research at the socio-technical intersections of computer science and social science with specific applications to managers in companies, teachers in schools and residents in cities.
cbsBDA's basic research program is aimed at modelling and explaining socio-technical interactions using set theory. Our applied research program seeks to design, develop and evaluate big data analytics applications for managers (descriptive, predictive, and prescriptive analytics), teachers (teaching analytics and learning analytics), and citizens (public health analytics).
Our current research, education, and consulting focuses on Big Social Data Analytics, GPS Analysis, Building Usage Analytics, and Bitcoin Blockchain Analytics.
cbsBDA aspires to conduct engaged scholarship in the Pasteur's Quadrant.
Our objective is not only to make seminal contributions to scientific knowledge as evidenced by peer-reviewed publications but also to create practical applications that yield meaningful facts, actionable insights, valuable outcomes, and sustainable impacts for organizations and society.
Reimann, P., Bull, S., Kickmeier-Rust, M., Vatrapu,R., & Wasson, B (Editors). (2015). Measuring and Visualizing Learning in the Information-Rich Classroom. Routledge, New York.
Vatrapu, R., Mukkamala, R., & Hussain, A. (under preparation/2018). Social Set Analysis. Springer Series on Computational Social Sciences, New York.
Flesch, B., Vatrapu, R., & Mukkamala, R. R. (2017). A Big Social Media Data Study of the 2017 German Federal Election Based on Social Set Analysis of Political Party Facebook Pages with SoSeVi. In Proceedings of 2017 IEEE International Conference on Big Data: BIGDATA (pp. 2638-2647).
Straton, N., Mukkamala, R. R., & Vatrapu, R. (2017). Big Social Data Analytics for Public Health: Predicting Facebook Post Performance Using Artificial Neural Networks and Deep Learning. In G. Karypis, & J. Zhang (Eds.), Proceedings of the 6th IEEE International Congress on Big Data. BigData Congress 2017 (pp. 89-96).
Egebjerg, N. H., Hedegaard, N., Kuum, G., Mukkamala, R. R., & Vatrapu, R. (2017). Big Social Data Analytics in Football: Predicting Spectators and TV Ratings from Facebook Data. In G. Karypis, & J. Zhang (Eds.), Proceedings of the 6th IEEE International Congress on Big Data. BigData Congress 2017 (pp. 81-88).10.1109/BigDataCongress.2017.20
Yin, H. S., & Vatrapu, R. (2017). A First Estimation of the Proportion of Cybercriminal Entities in the Bitcoin Ecosystem using Supervised Machine Learning. Proceedings of 2017 IEEE International Conference on Big Data: BIGDATA (pp. 3608-3617).
Vatrapu, R., Mukkamala, R. R., Hussain, A., & Flesch, B. (2016). Social Set Analysis: A Set Theoretical Approach to Big Data Analytics. IEEE Access. DOI: 10.1109/ACCESS.2016.2559584.
Flesch, B., Vatrapu, R., Mukkamala, R., & Hussain, A. (2015). Social Set Visualizer: A Set Theoretical Approach to Big Social Data Analytics of Real-World Events. Mining Social Data Workshop at the 2015 IEEE International Conference on Big Data (IEEE Big Data). Proceedings of the IEEE Computer Society, IEEE Press, IEEE Xplore.
Vatrapu, R., Hussain, A., Lassen, N. B., Mukkamala, R. R., Flesch, . B., & Madsen, R. (2015). Social Set Analysis: Four Demonstrative Case Studies. In A. Gruzd, J. Jacobson, P. Mai, & B. Wellman (Eds.), Proceedings of the 2015 International Conference on Social Media & Society. New York: Association for Computing Machinery. 10.1145/2789187.2789203
Mukkamala, R. R., Iskou Sørensen, J., Hussain, A., & Vatrapu, R. (2015). Social Set Analysis of Corporate Social Media Crises on Facebook. Proceedings of the IEEE Enterprise Computing Conference (EDOC 2015).
Jensen, T., & Vatrapu, R. (2015). Ships & Roses: A Revelatory Case Study of Affordances in International Trade. In J. Becker, J. vom Brocke, & M. De Marco (Eds.), ECIS 2015 Proceedings. AIS Electronic Library (AISeL).
Tørning, K., Jaffari, Z. A., & Vatrapu, R. (2015). Current Challenges in Social Media Management. In A. Gruzd, J. Jacobson, P. Mai, & B. Wellman (Eds.), Proceedings of the 2015 International Conference on Social Media & Society.  New York: Association for Computing Machinery. 10.1145/2789187.2789191
Zimmerman, C., Hansen, K., & Vatrapu, R. (2014). A Theoretical Model for Digital Reverberations of City Spaces and Public Places. International Journal of Electronic Government Research, 10(1), 46-62. 10.4018/ijegr.2014010104.
Kunst, K., & Vatrapu, R. (2014). Towards a Theory of Socially Shared Consumption: Literature Review, Taxonomy, and Research Agenda. In M. Avital, J. M. Leimeister, & U. Schultze (Eds.), ECIS 2014 Proceedings. AIS Electronic Library (AISeL).
Lassen, N. B., Madsen, R., & Vatrapu, R. (2014). Predicting iPhone Sales from iPhone Tweets. In M. Reichert, S. Rinderle-Ma, & G. Grossmann (Eds.), Proceedings of the IEEE 18th International Enterprise Distributed Object Computing Conference, EDOC 2014. (pp. 81-90). Los Alamitos, CA: IEEE. 10.1109/EDOC.2014.20
Hussain, A., Vatrapu, R., Hardt, D., & Jaffari, Z. A. (2014). Social Data Analysis Tool: A Demonstrative Case Study of Methodology and Software. In M. Cantijoch, R. Gibson, & S. Ward (Eds.), Analyzing Social Media Data and Web Networks. (pp. 99-118). Basingstoke: Palgrave Macmillan. 10.1057/9781137276773
Robertson, S., Vatrapu, R., & Medina, R. (2010). Off the Wall Political Discourse: Facebook Use in the 2008 U.S. Presidential Election. Information Polity, 15(1-2), 11-31. 10.3233/IP-2010-0196
Vatrapu, R. (2010). Explaining Culture: An Outline of a Theory of Socio-Technical Interactions. Proceedings of the 3rd International Conference on Intercultural Collaboration 2010, Copenhagen, Denmark August 19 - 20, 2010. (pp. 111-120). New York: ACM. 10.1145/1841853.1841871
Privatist PhD Student
Physical infrastructure of cbsBDA is in the form of one large room that houses on-premises servers and the eye-tracking equipment. Meeting rooms and open spaces for research purposes are available from the Department of Digitalization as well as central administration of CBS.
cbsBDA's IT infrastructure comprises of 2 virtual servers (Windows) hosted and supported by CBS IT, 4 amazon cloud servers (Línux) and eight physical servers (Windows & Linux) on-site at CBS and at the IT University of Copenhagen.
Scientific instrumentation at cbsBDA consists of a desktop eye-tracker (SMI RED 60Hz), eye-tracking glasses (SMI ETG-2), EEG headsets (Emotiv 16-channels), EDR wrist bands and three large-screen and high-resolution displays (3x84-inches display at 4K, 27-inches display at 5K, 6x 34-inch curved ultrawide monitors).