Although the discovery and analysis of communication patterns in large and complex email datasets are difficult tasks,
they can be a valuable source of information. We present EmailTime, a visual analysis tool of email correspondence
patterns over the course of time that interactively portrays personal and interpersonal networks using the correspondence
in the email dataset. Our approach is to put time as a primary variable of interest, and plot emails along a time line.
EmailTime helps email dataset explorers interpret archived messages by providing zooming, panning, filtering and
highlighting etc. To support analysis, it also measures and visualizes histograms, graph centrality and frequency on the
communication graph that can be induced from the email collection. This paper describes EmailTime's capabilities,
along with a large case study with Enron email dataset to explore the behaviors of email users within different
organizational positions from January 2000 to December 2001. We defined email behavior as the email activity level of
people regarding a series of measured metrics e.g. sent and received emails, numbers of email addresses, etc. These
metrics were calculated through EmailTime. Results showed specific patterns in the use email within different
organizational positions. We suggest that integrating both statistics and visualizations in order to display information
about the email datasets may simplify its evaluation.
Commercial websites offer many items to potential site users. However, most current websites display results of a search
in text lists, or as lists sorted on one or two single criteria. Finding the best item in a text list based on multi-priority
criteria is an exhausting task, especially for long lists. Visualizing search results and enabling users to perceive the
tradeoffs among the results based on multiple priorities may ease this process. To investigate this, two different
techniques for displaying and sorting search results are studied in this paper; Text, and XY Iconic Visualization. The
goal is to determine which technique for representing search results would be the most efficient one for a website user.
We conducted a user study to compare the usability of the two techniques. Collected data is in the form of participants'
task responses, a satisfaction questionnaire, qualitative observations, and participants' comments. According to the
results, iconic visualization is better for overview (it gives a good overview in a short amount of time) and search with
more than two criteria, while text-based performs better for displaying details.