Abstract
Complex network analysis is concerned with identifying statistically significant patterns in large and complex networks. A complex network is an abstract model of a complex system; it represents a well-chosen set of entities as nodes and one or more types of relationships between them as edges. Methods from complex network analysis have been used to identify small molecules called miRNAs that are able to stop breast cancer [13], to understand possible privacy breaches [9], or to analyze how humans solve complex problems [10]. As many areas in our globalized world tend to get more interconnected, the methods from complex network analysis became more important: for complex systems with an underlying network structure, the framework of complex network analysis provides the potential to identify central nodes, to describe deviating substructures, and to reveal the interaction between structure and function of complex networks. Based on this potential impact of network analysis on many fields of society, my work concentrates on understanding when to use which kind of network measure to analyze complex networks and where their limits are, a field I call network analysis literacy. This question can easily be generalized to data analysis literacy which can be even more generalized to the influence of our modern IT-systems on the individual, on organizations, and on society at large, which culminates in a new field of study called socioinformatics.
About the author
Katharina A. Zweig née Lehmann is a professor of theoretical computer science with a special emphasis on graph theory and the analysis of complex networks at the TU Kaiserslautern. After studying biochemistry and computer science at the University Tübingen (Germany), she worked at the ELTE University Budapest (Hungary) for two years in the biophysics group lead by T. Vicsek with a scholarship from the Deutsche Akademie der Naturforscher Leopoldina. She came back to Germany to lead an independent junior research group at the Interdisciplinary Center for Scientific Computing (IWR) at the University Heidelberg until she received her current position at the TU Kaiserslautern in April 2012. At the TU Kaiserslautern, she was responsible for the design of a new field of study called “Socioinformatics” which combines software engineering with input from sociology, economy, psychology, and philosophy to enable students to model the impact of IT systems on the individual, on groups, and on the society. For this effort she was honored with a juniorfellowship of the Gesellschaft für Informatik in 2013. She is also the current speaker of the juniorfellows.
TU Kaiserslautern Department of Computer Science Graph Theory and Complex Network Analysis Gottlieb-Daimler-Str. 48, room 670 67663 Kaiserslautern, Germany
©2014 Walter de Gruyter Berlin/Boston
