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«Abstract. Due to email’s ubiquitous nature, millions of users are intimate with the technology. However, most users are only familiar with managing ...»

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Using Rhythms of Relationships to

Understand Email Archives

Adam Perer,1,2 Ben Shneiderman,1,2 and Douglas W. Oard1,3

Human-Computer Interaction Lab, Institute for Advanced Computer Studies(1),

Department of Computer Science(2) or College of Information Studies(3),

University of Maryland, College Park, MD 20742

adamp@cs.umd.edu, ben@cs.umd.edu, oard@umd.edu

Abstract. Due to email’s ubiquitous nature, millions of users are intimate with the

technology. However, most users are only familiar with managing their own email, which is an inherently different task than exploring an email archive. Historians and social scientists believe that email archives are important artifacts for understanding the individuals and communities they represent. In order to understand the conversations evidenced in an archive, context is needed. In this paper, we present a new way to gain this necessary context: analyzing the temporal rhythms of social relationships. We provide methods for constructing meaningful rhythms from the email headers by identifying relationships and interpreting their attributes. With these visualization techniques, email archive explorers can uncover insights that may have been otherwise hidden in the archive. We apply our methods to an individual’s fifteen-year email archive, which consists of about 45,000 messages and over 4,000 relationships.

Introduction Since 1971, email has grown rapidly in popularity and has become a central part of many users’ personal and professional lives. Despite its impressive role in society, there are still few tools available to explore archives of email. The need for such tools will grow as valuable email archives increase in availability. The U.S. National Archives preserves emails as government records (Baron, 1999), a recently released collection of Enron emails has attracted significant public attention (Grieve, 2003), and some individuals have now accumulated email collections that span decades. Historians and social scientists will undoubtedly find these archives to be a valuable basis for understanding the individuals and organizations that created them. However, it is currently far from clear how these explorers will gain the context they need to understand the archive’s numerous conversations.

Figure 1 illustrates one way in which the universe of tools for interacting with online conversations can be subdivided. Email is created by individuals, and often in some organizational or social context. There has been a great deal of work on individual and organizational email productivity tools (regions A and B), and on the management and analysis of conversations in public email venues such as mailing lists and Usenet News (regions C and F). Our work in this paper focuses on region D, as we present new techniques for exploring the archived email of an individual.

Individual Organizational Social

Region A: Region B: Region C:

Managing an Managing current Managing current Current individual user’s email within an conversations in a current inbox organization public space

Region D: Region E: Region F:

Exploring an archive Exploring an archive Exploring an archive Archived of an individual’s of an organization’s of a public space.

messages messages Figure 1. Types of interactions with email collections.

Although the principal content of email is free text, when attempting to browse archives, the shortcomings of a text-only display become clear. Email archive explorers have previously tackled the archives by keyword searching, but this approach will often result in losing a conversation’s context (Donath, 2004).

Visualizations are one way to provide this missing context. In this paper, we show that valuable information can be uncovered by visualizing the temporal rhythms of social relationships that are evidenced in email archives. Each relationship that is evidenced in an email archive has a rhythm that can be characterized by the intensity of the correspondence over time. Relationships that are brief but intense have rhythms with sharp growth and steep decline.

Relationships that are durable and strong have consistent and continuing rhythms.

This paper presents insights achieved by analyzing the rhythms, which help archive explorers question why certain relationships start and stop, why certain relationships share similar activity patterns, and the nature of the relationships that yield different interaction patterns.

Detecting long-term rhythms, our focus in this paper, requires a collection spanning many years. Ben Shneiderman, a co-author of this paper and a pioneer in the fields of Human-Computer Interaction (HCI) and Information Visualization, has archived the emails he produced and received since 1984. The archive portrays over 4,000 of Shneiderman’s relationships, totaling around 45,000 messages. That archive spans a longer period than any other collection that was available to us when we started this work, offering us a unique opportunity to study the long-term rhythms of relationships present in a real email collection. In the next section, we review related work on interacting with online conversations. Next, we define what we mean by “relationships” and the “rhythms” that they produce. We then present our analysis methods and illustrate the use of those methods on the Shneiderman archive. Finally, we conclude with some suggestions for future work.

Previous Work In this section we briefly review prior work on email management, organizing the discussion using the task decomposition shown in Figure 1. Interaction with the user’s own current email (Region A) is by far the most actively studied email management task in the research literature. An early ethnographic study by Mackay in 1988 provided compelling evidence that different people deal with large quantities of their personal email in many different ways (MacKay, 1988).

Whittaker and Sidner’s later study resulted in the same conclusion, while also describing tasks that individuals use email for beyond the asynchronous communication for which it was designed (Whittaker and Sidner, 1996). Recent attempts to integrate visualizations into email clients seek to help users better manage their email. For example, enabling users to see the thread structure provides them with a better understanding of the how conversations evolve over time (Kerr, 2003; Venolia and Neustaedter, 2003). Another example is the Remail project, which provides a “correspondents’ map” that allows users to quickly see who they haven’t replied to recently, as well as a “message map” to see messages with similar attributes (Rohall et al., 2003).

Some recent projects have investigated exploration of personal email archives to uncover trends and patterns (Region D). PostHistory explored email archives that extend as far back as five years, seeking to support the development of insights that would be socially relevant to the owner of the email (Viegas et al., 2004). PostHistory featured an interface that animates over time to allow users to get a sense for their steady and intense relationships, and to illustrate fast-paced rhythms (e.g., resulting from project deadlines) and slower-paced rhythms (e.g., during vacations). Social Network Fragments, by contrast, focused on revealing groups of correspondents that emerge through email exchanges (Viegas et al., 2004). This interface also used time as a dimension to see how connections among correspondents appear and dissolve, thereby providing a way for the user to visualize the evolution of their own social network. In small studies, users were able to see meaningful patterns with both PostHistory and Social Network Fragments, sometimes using the visualization as instigation for telling stories.

The ubiquity and persistence of email has important consequences for the management of information within organizations (Region B). Ducheneaut and Bellotti studied the use of email in three organizations, and discovered that patterns of email use vary with individual roles within those organizations (Ducheneaut and Bellotti, 2001). They also noted that characteristics of each organization influenced the ways in which people used and organized their email collections. Tyler and Tang added to the understanding of email use within organizations, observing that responsiveness patterns vary in ways that reflect the dynamics of interpersonal relationships within an organization (Tyler and Tang, 2003). That observation led them to suggest that tools for estimating expected response latency could help users detect communication breakdowns. Another example of an organization tool is the “Email Mining Toolkit,” developed by Li et al. to support anomaly detection by creating behavior models. They then used these models to detect aberrant behavior of individuals or groups that may indicate abuse or policy violations (Li et al., 2004).

Exploration of archived collections of organizational email has also been studied (Region E). Tyler et al. used the social network analysis concept of “betweenness centrality” to identify communities in a large collection of email from a single organization, discovering that evidence of the management hierarchy for that organization could be found in the structure of the resulting graph (Tyler et al., 2003). Leuski’s “eArchivarius” system combined clustering based on content or co-addressing with activity timelines and biographies to explore activities in the U.S. National Security Council during the Reagan era using a small collection of declassified email messages (Leuski, 2003).

Usenet News, a distributed management system for a large collection of public mailing lists, has been archived since 1981. Mailing list usage differs somewhat from the use of personal email, both because privacy expectations are reduced and because the group-oriented communication structure alters interaction patterns. Smith used the “NetScan” system to study social accounting metrics for Usenet participation (Region F) and reported statistics on authorship and on activity over time (Smith, 1999; Smith, 2002). Usenet News is immediately available to both participants and nonparticipants (“lurkers”), which makes the distinction between management and exploration somewhat less defined than it is in the case of individual and organizational email. Users of the NetScan system can, for example, use it to find intense discussions and related “newsgroups” (Region C). Sack’s “Conversation Map” also explored Region C, focusing on the structure of long-term conversations by using social network diagrams, lists of discussion themes, and semantic network representations to support visualization of conversational structure and content (Sack, 2000).

The work described in this section is, of course, only a small sample of the extensive research on email utilization that has been reported since the first email was sent over the ARPANET in 1971. Looking broadly at that body of work, however, two trends emerge. First, the vast majority of the reported research has focused on managing current activities rather than on understanding what happened in the past. There has been much less work done in Regions D and E.

That makes sense, since only recently has email’s ubiquity become clear and archives of email are accruing. Second, the retrospective analyses on individual email (as opposed to mailing lists or Usenet News) that have been done have had limited scope; we are aware of only one study that has looked at even five years of email. In this paper, we take a longer view, looking back at a fifteen-year period that spans 1984-1998, as Internet email moved from adolescence to adulthood.

Relationships in Email Archives In this section, we describe the email collection that we worked with and the analytical framework that we applied to explore the long-term rhythm of relationships in that collection.

The Shneiderman Archive This archive begins in 1984; one year after Ben Shneiderman received tenure as an Associate Professor and founded the Human-Computer Interaction Lab at the University of Maryland. We chose to limit our study to the first fifteen years, culminating in 1998, because Shneiderman changed his email file structure significantly in 1999. The resulting set includes 44,971 messages. That is certainly not every email received or sent by Shneiderman during that period.

Rather, it includes those that Shneiderman purposefully stored. Although analysis of the results of intentional retention will not provide a complete picture of an individual’s email traffic, it does serve to filter out spam and other less significant messages. The saved email gives historians a picture of what Shneiderman felt at the time were the significant conversations in his professional life. However, our analysis will miss some subtle and friendly exchanges, which could also serve as sources of interesting rhythms (e.g., as described by (Tyler and Tang, 2003)).

Relationships Email provides a medium in which users may foster relationships with individuals, organizations, and a global community. Relationships are fundamental to any form of human interaction, so we have chosen to aggregate this collection by relationship rather than the more commonly studied granularities of “threads” (i.e., reply chains) or individual messages. Aggregation into relationships facilitates exploration by masking some sources of variation (e.g., multiple email addresses for a single individual or individuals that participate in multiple relationships) that might otherwise conceal the broad themes that we wish to uncover. By “relationships” we mean a set of conversations over time that reflects a type of interaction that was meaningful to the person that created the email archive. Examples could include conversations with a specific colleague, discussion of a particular topic (e.g., academic governance) involving several members of an organization, or a group of messages regarding the planning of an event (e.g., a professional conference).

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