1 Applications of Social Network Analysis (Introduction)

1 Applications of Social Network Analysis (Introduction) Thomas N. Friemel a In recent years Social Network Analysis (SNA) has increasingly been used as an approach in most scientific disciplines and has gained soaring attention by the public. It is difficult to identify a single reason to explain this prominence of SNA in academia, politics, business and our daily lives. Nevertheless this introduction tries to indicate in a first step what social network analysis is and how it developed. Some explanations for the increased use of SNA are suggested in a second step and a third part gives an outlook to the contributions compiled in this volume. 1.1 Defining Elements of SNA What makes social network analysis to what it is? Freeman (2004) identifies four definitive features of social network analysis: structural intuition, systematic relational data, graphic representation and mathematical or computational models. He then traces back the four features to their scientific roots. Early structural intuitions can be found in the work of August Comte (1853), Henry Maine (1861) and Ferdinand Tönnies (1855). The first documented collection of systematic empirical data is dated even earlier (1802), when Pierre Huber published a detailed description of the dominance behaviour of bumblebees. If we exclude tree-based images of kinship (ninth century), the first graphical representations of relational data are from Lewis Henry Morgan (1851), Alexander Macfarlane (1883) and John Hobson (1884). Finally the mathematical (computational) models complete the set of basic components. One of the mathematical foundations is graph theory, which is based on the work by Leonard Euler (1736). Other important a Institute of Mass Communication and Media Research at the University of Zurich; Switzerland, th.friemel@ipmz.uzh.ch 13

Thomas N. Friemel contributions were made by Irénée Bienaymé (1845) on stochastic models of kinship and Macfarlane (1883) on mathematical notation of English law. The striking insight of this historical overview provided by Freeman (2004) is that although all four defining elements were given by the end of the 19 th century, it took several decades before sociometry arose generally cited as the beginning of social network analysis. 1.2 Recent Changes in SNA It seems that history is repeating itself in the 20 th century. Although many of the central concepts were known for years, the integration into the various academic fields was only moderate. Wasserman, Scott and Carrington date the beginning of the rapid increase in interest in SNA in the 1990s (2005: 1). The tipping point in public awareness can roughly be dated to the turn of the millennium. The most public attention was received by physicists (Albert, Barabasi, Watts) and mathematicians (Strogatz) regarding their work on small world (Barabasi/Albert, 1999; Watts/Strogatz, 1998). Unfortunately they did not reflect earlier work done in this field, which has lead to a longlasting split between the physicists and the rest of the social network community. This split can be clearly seen by analyzing the citation patterns of the social network literature (Freeman, 2004: 166). Although the history of SNA dates back several decades, the methods for SNA continue to develop at an impressive speed, and conference presentations are sometimes introduced as the bleeding cutting edge (Butts, 2007). Nevertheless, few researchers are working on the methodological cutting edge, while the lion s share of network researchers are applying familiar concepts like centrality measures, triad census, block modelling and various ways of clustering. Therefore the increasing interest in SNA can only partially be explained by recent innovation in mathematical and computational representation or by any other of the defining elements (structural intuition, systematic relational data and graphic representation). The most important change may be the availability of easily applicable software programs (Huisman/van Duijn, 2005). Social Network Analysis has been customised by software programs and is increasingly included in university curricula. These are probably the major reasons for its rise in prominence. Methodological innovations are usually driven by a theoretical research question (a substantial problem). This holds true for SNA given structural intuition as one defining element. However, the most interesting dynamic occurring in today s SNA goes in the reverse direction: from methodology to 14

Applications of Social Network Analysis theory. Inspired by the potential of measures and procedures, scientists are developing new research questions and even theories structural theories. The highly interdisciplinary conferences on SNA provide excellent opportunities for this development by bringing together very different scientific fields. This reversed research sequence and the cross stimulation by the different fields can be seen as other reasons for the increasing use of SNA. The idea that actors are embedded in a context and that this context might influence the behaviour of the actors is not new. To what extent the actors are individually motivated and how strong a network influences (or determines) their behaviour is a long standing discussion in the respective fields. Social Network Analysis helps us to address this question with appropriate theory and methodology. The increasing popularity of SNA may be seen as evidence that it provides additional explanatory power. Of course this argumentation is rather weak. It is not sufficient to prove the usefulness of SNA by demonstrating its increasing use. But when we try to answer the question why there is an increasing use of SNA, the additional explanatory value is one reasonable answer. Beside this superiority argument of SNA as a new research perspective, we can also think of a change in object. If the objects under investigation evolved into networks in which actors are increasingly dependent on their structural embedding, SNA is simply more appropriate. Therefore a further explanation for the rising prominence of SNA would be that the world changed in a way that has allowed SNA to become the most promising research approach. 1.3 Selected Applications of SNA Regardless of the reason for the increasing interest in SNA, it needs a platform. This volume includes selected papers presented at the 3 rd conference on Application of Social Network Analysis held in October 2006 (ASNA 2006). This 3 rd conference at the University of Zurich was hosted by the Institute of Mass Communication and Media Research. ASNA 2006 primarily provided an interdisciplinary venue with a focus on the applications of social network analysis; however, contributions on theoretical and methodological issues regarding SNA were also presented. Although the papers in this volume provide a good sample of this wide spectrum of applications, there are many more topics covered in today s SNA. Several more examples can be found on the conference website of ASNA 2006 and ASNA 2007 (www.ipmz.uzh.ch/asna) as well as the homepage of the International Network for Social Network Analysis (www.insna.org). 15

Thomas N. Friemel The first paper by Marina Hennig addresses the question of the circumstances under which social relations can become a resource. She also challenges the widely known idea of the strength of weak ties (Granovetter, 1973). Based on a sample of 1.953 German families, the paper shows that it might not be the strength of the tie which makes weak ties so important but rather the heterogeneity of the network that potentially becomes a resource for the individual. Tevfik Erdem and Nail Oztas analyse the friendship and study networks of 313 public-administration students. They address the topic of social capital, probably the most discussed field within SNA in recent years. Erdem and Oztas apply different theoretical approaches to social capital and explore possible ways of integrating them. Following the first two papers, in which the importance and different characteristics of social networks are discussed, the third paper by Ines Mergel and Thomas Langenberg addresses the question as to which factors lead to the creation, maintenance, decay and reconnection of online network ties. Online network ties are understood as part of our virtual life which is increasingly organized by various online social-networking sites where users maintain their online profile, including their connections to other persons. The theoretical framework presented in their paper includes various aspects assumed to influence the lifespan of online network ties, which include personal, dyadic, structural and content-related characteristics. In contrast to the first three papers, the paper by Nicholas Silburn includes not only networks of individuals but also interactions between actors and information systems. Silburn provides a theoretical outline on how people share information with others and on how they use information systems to accomplish their job. An exploratory analysis of two teams provides first empirical insights. Karin Ingold s paper turns to the implications of social networks on politics. She analyses the influence of actors coalition on policy choices in the case of Swiss climate policy. Her paper also indicates how social network analysis can be combined with other methods such as multicriteria analysis. The range of possible applications of social network analysis in politics is of course not restricted to the national level. Zeev Maoz, Ranan Kuperman, Lesley Terris and Ilan Talmud analyse how national network centrality is related to their involvement in international conflicts. This discussion is based on data ranging from 1816 to 2001. Unfortunately the term network has become very prominent in the realm of terrorism and has demonstrated that traditional organization structures (i.e. armed forces) might have serious problems when facing an unconventional organization like a diffuse terror network. At the same time the infrastructure 16

Applications of Social Network Analysis of western society has evolved to networks. This especially holds true for transportation networks like underground systems. Ferenc Jordán s paper shows that there is strong evidence that the bombing of the London underground system in July 2005 was based on network analytical calculations. 1.4 References Barabasi, A.-L./Albert, R., 1999, Emergence of Scaling in Random Networks, Science 286, 509-512. Bienaymé, I.-J., 1845, De la loi de multiplication et de la durée des families, Bulletin de la Société Philomathique de Paris, 37-39. Butts, C., 2007, Network Inference from Unstructured Sources, Presentation at the 27th International Sunbelt Social Network Conference, May 1-6, 2007, Corfu, Greece. Comte, A., 1830-1842, Cours de philosophie positive, J.B. Baillière et Fils, Paris. Euler, L., 1736, Mechanica sive motus scientia analytice exposita. Freeman, L.C., 2004, The Development of Social Network Analysis, A Study in the Sociology of Science, Empirical Press, Vancouver (BC). Granovetter, M.S., 1973, The Strength of Weak Ties, The American Journal of Sociology 78/6, 1360-1380. Hobson, J.A., 1884, The Evolution of Modern Capitalism, A Study of Machine Production, Allen & Unwin, Macmillan, London/New York. Huber, P., 1802, Observation on Several Species of the Genus Apis, known by the Name of Humble Bees, and called Bombinatrices by Linneaus, Transactions of the Linnean Society of London 6, 214-298. Huisman, M./van Duijn, M.A.J., 2005, Software for Social Network Analysis, In: Carrington, P.J./Scott, J./Wassermann, S., Models and Methods in Social Network Analysis, Cambridge University Press, Cambridge, 270-316. Macfarlane, A., 1883, Analysis of Relationships of Consanguinity and Affinity, Journal o the Royal Anthropological Institute of Great Britain and Ireland 12, 46-63. Maine, H., 1861, Ancient Law, Oxford University Press, London. Morgan, L.H., 1851, Systems of Consanguinity and Affinity of the Human Family, Smithsonian Institution, Washington, DC. Tönnies, F., 1887, Gemeinschaft und Gesellschaft, Grundbegriffe der reinen Soziologie, Fues, Leipzig. Wasserman, S./Scott, J./Carrington, P., 2005, Introduction, In: Carrington, P./Scott, J./Wassermann, S., Models and Methods in Social Network Analysis, Cambridge University Press, 1-7. Watts, D.J./Strogatz, S.H., 1998, Collective Dynamics of Small World Networks, Nature 393, 440-442. 17