Balancing Systematic and Flexible Exploration of Social Networks

Social network analysis (SNA) has emerged as a powerful method for understanding the importance of relationships in networks. However, interactive exploration of networks is currently challenging because: (1) it is difficult to find patterns and comprehend the structure of networks with many nodes and links, and (2) current systems are often a medley of statistical methods and overwhelming visual output which leaves many analysts uncertain about how to explore in an orderly manner. This results in exploration that is largely opportunistic. Our contributions are techniques to help structural analysts understand social networks more effectively. We present SocialAction, a system that uses attribute ranking and coordinated views to help users systematically examine numerous SNA measures. Users can (1) flexibly iterate through visualizations of measures to gain an overview, filter nodes, and find outliers, (2) aggregate networks using link structure, find cohesive subgroups, and focus on communities of interest, and (3) untangle networks by viewing different link types separately, or find patterns across different link types using a matrix overview. For each operation, a stable node layout is maintained in the network visualization so users can make comparisons. SocialAction offers analysts a strategy beyond opportunism, as it provides systematic, yet flexible, techniques for exploring social networks

1 Introduction

Understanding networks is an inherently difficult process. It is difficult to visualize, navigate, and most problematic, find patterns in networks. Despite all of these challenges, the network perspective is appealing. Network analysts focus on relationships instead of just the individual elements; how the elements are put together is just as important as the elements themselves. Prior to this perspective, social research focused largely on attributes and neglected the social part of behavior (how individual interact and the influence they have on each other) [12]. Using techniques from the social network community, analysts can find patterns in the structure, witness the flow of resources through a network, and learn how individuals are influenced by their surroundings.