Who talks to whom: an evaluation of a call log visualization
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R E G UL A R P A P E R
Valerie Riegler • Lina Wang • Johanna Doppler-Haider • Margit Pohl
Who talks to whom: an evaluation of a call log visualization
Received: 14 February 2020 / Revised: 9 June 2020 / Accepted: 25 June 2020 Ó The Author(s) 2020
Abstract Adding temporal information to social network visualizations is still a challenging task despite previous research efforts. Visualizing call logs on an event-based level can show various attributes of a connection. The dimension time is of great interest to analysts as it offers insights into trends and patterns such as changing relationships between different actors or economic opportunities for businesses. Yet current approaches suffer from limitations that can be improved with the visualization design presented in this work. Our presented visualization was developed considering aesthetic criteria and characteristics of adjacency matrices and node-link diagrams. A heuristic evaluation according to these criteria was conducted. In a formative evaluation process, an artificial dataset was specifically created to examine dynamic social networks. A qualitative user study with observation and think-aloud protocols was conducted and analyzed with regard to the user’s strategies, limitations of the visualization and potential additional features. The visualization appears to be suitable for all of the evaluated network tasks; however, path-related tasks were more challenging than other tasks. Keywords Spatiotemporal visualization Dynamic social networks Communication network Qualitative evaluation
1 Introduction Social network analysis has become increasingly important for researchers, businesses and individuals. It offers insight into group structure, relationships between the different actors such as friends, business partners, criminals, etc. and makes it possible to find influential actors or connections between people as Ahn et al. (2011) argue. The communication between individuals is increasingly mediated by computer technology due to the technological advances in the last decades. The various forms of digital communication, such as phone calls, SMS messages, emails, chat rooms and social networks (e.g., Facebook or Twitter), leave a digital trace that tie the individuals, groups and objects to one another which is described by Smith et al. (2009). These digital
V. Riegler L. Wang J. Doppler-Haider (&) M. Pohl Institute of Visual Computing & Human-Centered Technology, Vienna University of Technology, Vienna, Austria E-mail: [email protected] V. Riegler E-mail: [email protected] L. Wang E-mail: [email protected] M. Pohl E-mail: [email protected]
V. Riegler et al.
traces can be used to depict the social network among the individuals. According to Ghoniem et al. (2004), an intuitive approach to visualize relations is to use links between the actors to show who is connected to whom (e.g., a node-link diagram where nodes represent the actors). Researchers have also come up with other ways to visualize soc
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