Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.

Abstract not found

Many on-line interaction environments have a large number of users. It is difficult for the participants, especially new ones, to form a clear mental image about those with whom they are interacting. How can we compactly convey information about these participants to each other? We propose the data portrait, a novel graphical representation of users based on their past interactions. Data portraits can inform users about each other and the overall social environment. We use a flower metaphor for creating individual data portraits, and a garden metaphor for combining these portraits to represent an on-line environment. We will review previous work in visualizing both individuals and groups. We will then describe our visualizations, explain how to create them, and show how they can be used to address user questions. KEYWORDS: Information visualization, data portraits, user-centered visualization, interaction context.

Abstract not found

We introduce a network visualization technique that supports an analytical method applied in the social sciences. Policy network analysis is an approach to study policy making structures, processes, and outcomes, thereby concentrating on relations between policy actors. An important operational concept for the analysis of policy networks is the notion of centrality, i.e., the distinction of actors according to their importance in a relational structure. We integrate this measure in a layout model for networks by mapping structural to geometric centrality. Thus, centrality values and network data can be presented simultaneously and explored interactively.

views and conclusions contained in this document are those of the authors and should not be

We propose a novel visualization approach that facilitates graphical exploration and communication of relative actor status in social networks. The main idea is to map, in a drawing of the entire network, actor status scores to vertical coordinates. The resulting problem of determining horizontal positions of actors and routing of connecting lines such that the overall layout is readable is algorithmically difficult, yet well-studied in the literature on graph drawing. We outline a customized approach. The advantages

Abstract not found

Abstract. This paper describes a within-subjects experiment in which we compare the relative effectiveness of five sociogram drawing conventions in communicating underlying network substance, based on user task performance and usability preference, in order to examine effects of different spatial layout formats on human sociogram perception. We also explore the impact of edge crossings, a widely accepted readability aesthetic. Subjective data were gathered based on the methodology of Purchase et al. [14]. Objective data were collected through an online system. We found that both edge crossings and conventions pose significant effects on user preference and task performance of finding groups, but either has little impact on the perception of actor status. On the other hand, the node positioning and angular resolution might be more important in perceiving actor status. In visualizing social networks, it is important to note that the techniques that are highly preferred by users do not necessarily lead to best task performance. 1

Abstract not found