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Revealing Communication Patterns in an Online Dating System Abstract Social visualizations are powerful tools both for users of mediated communication systems seeking social context and for researchers seeking insights into user behavior. This paper describes a visualization tool built to support research into patterns of communication among 50,000 of users of an online dating system, featuring geographic and categorical variable layouts overlaid with individual communications. Keywords Online personals, online dating, social visualization, computer-mediated communication ACM Classification Keywords H5.3. Group and Organization Interfaces; Asynchronous interaction; Web-based interaction. Introduction Good social visualizations reveal patterns of interaction that would otherwise be hard to perceive. In the best social visualizations, these patterns provide insight to participants trying to make sense of a social milieu or researchers trying to understand the dynamics in terms of a theory or hypothesis. Copyright is held by the author/owner(s). CHI 2006, April 22–27, 2006, Montreal, Canada. ACM 1-xxxxxxxxxxxxxxxxxx. Andrew T. Fiore School of Information University of California, Berkeley 102 South Hall Berkeley, CA 94720-4600 USA [email protected]

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  • Revealing Communication Patterns in an Online Dating System

    Abstract Social visualizations are powerful tools both for users of mediated communication systems seeking social context and for researchers seeking insights into user behavior. This paper describes a visualization tool built to support research into patterns of communication among 50,000 of users of an online dating system, featuring geographic and categorical variable layouts overlaid with individual communications.

    Keywords Online personals, online dating, social visualization, computer-mediated communication

    ACM Classification Keywords H5.3. Group and Organization Interfaces; Asynchronous interaction; Web-based interaction.

    Introduction Good social visualizations reveal patterns of interaction that would otherwise be hard to perceive. In the best social visualizations, these patterns provide insight to participants trying to make sense of a social milieu or researchers trying to understand the dynamics in terms of a theory or hypothesis.

    Copyright is held by the author/owner(s).

    CHI 2006, April 2227, 2006, Montreal, Canada.

    ACM 1-xxxxxxxxxxxxxxxxxx.

    Andrew T. Fiore

    School of Information

    University of California, Berkeley

    102 South Hall

    Berkeley, CA 94720-4600 USA

    [email protected]

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    The organizers of this workshop categorize social visualizations by whether they depict physical or virtual worlds and by the modality of communication (text, audio, video). I would like to elaborate on this typology I believe it is important also to consider the scope and point of view of the visualization. Scope indicates the breadth of the data presented; most salient is whether the data (behaviors, emails, etc.) represent a global or local collection that is, are these data the product of an individual or the entire population? Does the user have access to data beyond her own? Relatedly, the point of view of the visualization describes how the display relates to the user: is it an ego-centric or omniscient point of view? Although scope and point of view are intertwined, they remain distinct. We can conceive of an ego-centric presentation of social information that is nonetheless global, incorporating everyone's behavior. End users undertaking social tasks are more likely to benefit from ego-centric visualizations with either global or local data; the omniscient bird's-eye view may be more complex than necessary to help them navigate a social world, for which just-in-time, just-in-place information would likely suffice and be easier to understand. On the other hand, global, omniscient social visualizations are the kind most often used by researchers studying mediated communication.

    Studying Online Dating The visualization I will describe here is a researcher's tool that I built to facilitate the study of user behavior in an online dating system (Fiore & Donath 2004). It provides an omniscient, global perspective on the communications among more than 50,000 users of this heterosexual online dating system. At its core, this

    visualization organizes the users according to some spatial conceit and then overlays the communications among them as thin, transparent lines.

    Geographic View I began the system as a geographic visualization, plotting users by their location in the United States or Canada (Figure 1). Because the colored points representing users accumulate color intensity as the number of users in the same location increases, this view has the advantage of revealing the density of users in various cities and regions. I then overlaid each email sent from one user to another through the dating system as a thin, transparent line. These, too, accumulate in intensity, so common communication paths are brighter than rare ones. However, communication patterns in a visualization of North America do not provide much insight because most communications in online dating occur over short distances that become vanishingly small on a map that spans the continent.

    Categorical Density View Online dating systems collect a great deal of demographic and personal information from their users. Taking advantage of this information proved essential to the development of a visualization useful for making sense of communication patterns among the online dating users.

    Presenting two continuous, numerical variables in a two-dimensional scatterplot is a common way to reveal how they co-vary. Doing this with two categorical variables is unusual and somewhat problematic. However, the most interesting descriptive characteristics from the online dating system I studied

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    were categorical for example, race, religion, and education. To show the population of users according to two categorical variables, I used categorical density plots. Specifically, I divided the space in the plot according to the intersection of the levels of each variable, then filled in the intersections with randomly scattered points representing users who posses both of the intersecting qualities. As a result, those intersections of two categorical qualities that contain a greater proportion of the population will appear denser than those that contain less of the population. Figure 1 shows such a plot for the categorical variables sex and marital status. This plot reveals that most users are divorced or never married and that these characteristics do not differ noticeably by sex.

    WHOS TALKING WITH WHOM? Whereas the overlaid communication lines were not particularly useful in the geographic layout because they represented unusual cases (long-distance communications), they are integral to the usefulness of the categorical layout. The patterns of communication lines reveal which groups of people, as defined by the intersecion of the two categorical characteristics, are communicating with each other. In Figure 2, a glance shows that most communications occurred between two divorced users or two who had never been married. That is, there was less between-group than within-group communication. There is another, more subtle pattern evident as well there are more widowed

    woman than men, and these women seem to communicate primarily with divorced men. Observations like this drove the development of a methodology (described in Fiore & Donath 2005) for quantifying the degree to which communicating dyads in this online dating system tend to share the same value for a given categorical variable. A similar style of pairwise analysis has emerged recently as well in social psychology, where it is used to characterize the importance of various kinds of similarity and dissimilarity among romantic couples (e.g., Klohnen & Mendelsohn 1998).

    References [1] Donath, J.S., Karahalios, K., & F.B. Viegas. Visualizing Conversations. In Proc. HICSS 32, 1999.

    [2] Fiore, A.T., & J.S. Donath. Homophily in Online Dating: When Do You Like Someone Like Yourself? Short paper, Computer-Human Interaction 2005.

    [3] Fiore, A.T., and J.S. Donath. Online Personals: An Overview. Short paper, Computer-Human Interaction 2004.

    [4] Klohnen, E.C., & G.A. Mendelsohn. Partner Selection for Personality Characteristics: A Couple-Centered Approach. In Personality and Social Psychology Bulletin 24 (3), March 1998, pp. 268-278.

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    Figure 1 (above). Geographic view of online dating users. At bottom, communications among users have been overlaid as thin, transparent lines. Color intensity of points and lines indicates the relative quantity of people and communications.

    Figure 2. Categorical density plots showing online dating users according to marital status and sex. At bottom, communications have been overlaid as in Figure 1.