Design and analysis of socio-technical systems

The pervasive use of information and communication technologies across all fields of society results in an increasing interdependency between social and technical systems. Modern society depends on a multitude of technical systems and infrastructures, moreover many of those technical systems are influenced by the social systems into which they are embedded. Obvious examples for such systems include communication systems, collaboration tools, crowdsourcing platforms, social media or collaborative information systems, while less obvious examples include software engineering projects, search engines, traffic and power infrastructures or companies. Acknowledging the fact that the social and the technical layers of such systems are coupled inseparably, they are commonly referred to as socio-technical systems. The fact that their study necessitates models for both the social and the technical dimension has recently been acknowledged by a number of research communities and related research questions are addressed under the umbrella of socio-technical, techno-social or cyber-physical systems, community informatics, social informatics, human-computer interaction and social computing.

Importantly, the ongoing convergence between social and technical systems implies that there is an increasing amount of data that can be used to quantitatively study socio-technical systems. Our focus is thus on data-driven research which allows us to analyse socio-technical systems in different contexts, typically addressing the question how they can be designed and managed better.

Studying the interplay between social structures and information networks found in scholarly publications, one important question that we study is how social structures influence our perception of what is important and how do they influence what we perceive and what we ignore. In this line of research we have shown that scholarly citation structures are indeed highly correlated with the social network between authors. This correlation can be used to predict - solely based on the collaboration network of authors - whether their publications will be among the most highly cited in their respective field. This work not only provides interesting insights into citation patterns, it also suggests novel directions for the development of importance measures and ranking schemes which take into account the social dimension of information systems.

Figure: Citation (left) and collaboration (right) structures of a scientific community. Each node represents one author in the author-author citation network (left) and the coauthorship network (right)

Interestingly for many of today's socio-technical systems, the proper "design" and "functioning" of the social component is as important as that of the technical component. In another line of research we thus study questions such as how technical systems can help us to monitor or even optimise the evolving social structures of teams or companies. We typically address this problem from the perspective of complex networks, which allows us to employ our competence in the modeling of evolving networks, the network-based analysis of collaboration structures, or the analysis of time-varying networks. Similarly, we are finally interested in novel approaches which facilitate the design of socially-aware technical systems, i.e. technical systems that actively utilise the structure and dynamics of the social systems that they are coupled with in order to achieve their goals. Particular examples include trust-based systems which can be used in the context of Peer-to-Peer or social recommender systems.

Again, a particular asset of our research on the design and analysis of socio-technical systems is that it is truly interdisciplinary, combining the perspectives of social sciences, computer science and complex systems. The success of this approach is documented by the fact that our publications have been published in interdisciplinary journals like EPJ Data Science, in top-tier computer science venues like the International Conference on Software Engineering or IEEE TrustCom, as well as in publications which specifically address the interplay between social sciences and computer science.

 

Selected Publications

Quantifying and suppressing ranking bias in a large citation network

[2017]
Vaccario, Giacomo; Medo, Matus; Wider, Nicolas; Mariani, Manuel S.

arxiv:1703.08071

more»

The Social Dimension of Information Ranking: A Discussion of Research Challenges and Approaches

[2014]
Scholtes, Ingo; Pfitzner, Rene; Schweitzer, Frank

Socioinformatics - The Social Impact of Interactions between Humans and IT

more»

Predicting Scientific Success Based on Coauthorship Networks

[2014]
Sarigol, Emre; Pfitzner, Rene; Scholtes, Ingo; Garas, Antonios; Schweitzer, Frank

EPJ Data Science, pages: 9, volume: 3

more»

Social resilience in online communities: The autopsy of Friendster

[2013]
Garcia, David; Mavrodiev, Pavlin; Schweitzer, Frank

Proceedings of the 1st ACM Conference in Online Social Networks (COSN'13)

more»

Resilience in Enterprise Social Networks

[2013]
Burger, Valentin; Hofeld, Tobias; Garcia, David; Seufert, Michael; Scholtes, Ingo; Hock, David

In Proceedings of Informatik 2013, 43. Jahrestagung der Gesellschaft für Informatik e.V. (GI), Informatik angepasst an Mensch, Organisation und Umwelt, 16.-20. September 2013, Koblenz

more»

The co-evolution of socio-technical structures in sustainable software development: Lessons from the open source software communities

[2012]
Zanetti, Marcelo Serrano

ICSE '12 Proceedings of the 34th International Conference on Software Engineering

more»

A tunable mechanism for identifying trusted nodes in large scale distributed networks

[2012]
Chandra, Joydeep; Scholtes, Ingo; Ganguly, Niloy; Schweitzer, Frank

Proceedings of 11th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom 2012)

more»

Coping with information overload through trust-based networks

[2008]
Walter, Frank Edward; Battiston, Stefano; Schweitzer, Frank

Managing Complexity: Insights, concepts, Applications

more»