Towards a Model of Interdisciplinary Teamwork for Web Science: What can Social Theory Contribute? Peter Kraker Know-Center Inffeldgasse 13, 8010 Graz (Austria) pkraker@know-center.at Sebastian Dennerlein Know-Center Inffeldgasse 13, 8010 Graz (Austria) sdennerlein@know-center.at ABSTRACT In this position paper, we argue that the different disciplines in Web Science do not work together in an interdisciplinary way. We attribute this to a fundamental difference in ap- proaching research between social scientists and computer scientists, which we call the patterns vs. model problem. We reason that interdisciplinary teamwork is needed to overcome the patterns vs. model problem. We then discuss two theoretical strains in social science which we see as relevant in the context of interdisciplinary teamwork. Final- ly, we sketch a model of interdisciplinary teamwork in Web Science based on the interplay of collaboration and cooper- ation. Author Keywords interdisciplinary teamwork, paradigms, collaboration, co- operation, patterns, models, web science ACM Classification Keywords J.4 [Social and Behavioral Sciences]; K.3 [Computers and Education] 1. INTRODUCTION Each scientific discipline has its own culture. Kuhn (1962) called these cultures “paradigms” – a combination of as- sumptions, theories, and methods that guide research in a discipline. At times, a new set of problems arises that can- not be answered with the standard paradigm of a single dis- cipline. Instead, these problems require knowledge from different disciplines. As a result, new formations emerge: interdisciplinary fields. Web Science is such an interdisciplinary field. When the World Wide Web became social, studying people's online behavior became as interesting as building the infrastruc- ture that allow for these interactions to take place [7]. In order to address the questions raised by Web Science, com- puters scientists need to talk to social scientists; social sci- entist need to talk to jurists – and sometimes they all need to talk to each other to solve a common goal. One of the major problems of contemporary Web Science is that the different disciplines do not work together in an in- terdisciplinary way. Researchers often do not build on each other’s strengths but they are rather suspiciously looking at each other’s results. Social scientists tend to disregard com- puter scientists’ results because they are not grounded in theory. Computer scientists tend to disregard social scien- tists’ results because they are not based on big datasets. When people from different scientific cultures and the cor- responding paradigms get together, they surely have prob- lems comprehending each other. They come from a differ- ent background, have a different vocabulary, and a different methodology. We, however, argue that Web Science suffers from a problem that goes beyond differences in methods or terminology and a mere new combination of existing para- digm parts. This problem deals with a fundamental differ- ence in approaching research, and affects many other inter- disciplinary fields where computer scientists and social scientists in a wider sense (sociologists, psychologists, learning scientists etc.) have to work together. We call it the models vs. patterns problem. In this paper, we discuss this fundamental problem and sketch a model grounded in so- cial theory to overcome this problem. 2. THE PATTERNS VS. MODELS PROBLEM To understand the way that computer scientists approach research, it is worthwhile to look at the area of knowledge discovery in databases (KDD). In 1996, Fayyad et al. de- fined the goal of KDD as to find new, valid, useful, and understandable patterns in data [5]. After preprocessing and data selection, the researcher performs some sort of data mining method (e.g. clustering or machine learning). The output of the data mining step are the aforementioned pat- terns. In a next step, the researcher evaluates the patterns and thus gains knowledge. This process does not only describe KDD, it describes the way that a lot of computer scientists do research. Starting from a certain problem, they try to find patterns that relate to that problem in a big dataset. There is a certain caveat to the given definition of knowledge, and Fayyad and his col- leagues make it very clear: „[..] knowledge in this definition Copyright is held by the author/owner(s). Web Science 2013 Workshop: Harnessing the Power of Social Theory for Web Science. May 1, 2013, Paris, France.