The Course focuses on structures of human groups, such as communities, institutions, industries, markets, countries, and blocs. These structures are conceptualized as networks of ties. The ties are the main variable of interest, because they transmit behavior, services, information or materials. The patterns of ties in any one network also provide insights into the entities linked by them. Therefore, the course addresses the concept of network, introducing several types of networks and the ways in which they can be modeled and analyzed visually and computationally. Techniques that combine relational data (such as links) with nonrelational attributes of entities (such as entity-specific economic indices) are discussed. The nonrelational attributes enhance interpretations of network structure and also enable increasingly focused analyses of subnetworks (say, the trade flows between a particular set of countries situated within a wider trade bloc).
Collective norms, shared strategies, industrial cohesion, market attitudes, and similar behavior emerge from relations between organizational entities. A major concern of organizational network analysis is to investigate who is related and who is not, and why. The Course introduces a variety of techniques to detect cohesive subgroups based on the underlying structure of respective networks.
These techniques comprise means to various ends, rather than an end in themselves, and are used throughout the Course as complements to advanced analyses. Furthermore, they enable tests of whether structurally delineated groups differ with respect to various nonrelational attributes. The Course tackles the differences between, and the implications of, grouping entities according to structural properties and non-network attributes. It introduces a variety of network and subnetwork measurements of cohesion, as well as analyses that help identify components according to various criteria. Methods are also introduced for analyzing and optimizing the composition of teams, alliances, and coalitions.
Networks are structures that allow for the transport and exchange of information, services, and materials. In this perspective, familiarization with network structure helps explain diffusion of anything, from a product innovation to a disease. Some sections of networks permit rapid diffusion, whilst others act as bottlenecks. In addition, the position of specific entities in networks gives them social capital, competitive advantages, or allows them to assume a variety of brokerage roles. Such positions may put pressure on certain entities, but can also yield power and profit. The Course introduces various indices of centrality and centralization, as well as various interpretations of these important concepts along with their respective computational techniques. The distinction between an ego-centered and a socio-centered approach to centrality analyses is discussed in depth with associated modeling methodology and analytical tools. The quantitative and qualitative value of links between entities is then introduced as a means for understanding and computing various indices of social capital. A structural approach to the analysis of competition is introduced as a significant complement to other approaches toward this issue. Finally, the Course discusses and models diffusion processes that underlie social, organizational, communicative, administrative, and marketing behavior. The modeling of diffusion through networks is introduced, with a focus on investigating structural positions of entities, their relations, and their diffusion and adoption behavior.
Instructor Ion Georgiou
Course Date & Time
September 9 - November 18, Wednesdays, 21.00- 22.30 in Saõ Paulo, Brazil [Check the time in your timezone ]
No class on October 21 (Global Network Week).