(In)visible partners: People, Algorithms, and Business Models in Online Dating

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ELIZABETH CHURCHILL and ELIZABETH S. GOODMAN

A confluence of personal, technical and business factors renders priorities, practices, and desires visible – and invisible – when people use online dating sites to look for partners. Based on a review of websites, interviews with dating site designer/developers, and interviews with would-be daters about their online experiences and their first dates, we offer some insights into the entanglement between daters, site implementers, and business models that is part and parcel of getting ‘matched’ via the Internet. We also examine the role of the website interface and match algorithms in the expression of the “real me” and the search for “the one” – and then how processes of self-presentation and partner imagination play into the planning, expectation-setting and experience of the first date. Finally, we reflect on issues raised for design and for strategic technology development. This study of online-offline encounters is an example of using detailed qualitative analyses to deliver deeper understandings of people’s experiences, offering a complement to large-scale, aggregated data summaries based on website activity logs and surveys.

  1 comment for “(In)visible partners: People, Algorithms, and Business Models in Online Dating

  1. September 26, 2017 at 4:07 pm

    […] The first is "Numbers Have Qualities Too: Experiences with Ethnomining” by Ken Anderson, Dawn Nafus, Tye Rattenbury, and Ryan Aipperspach. In this paper the authors discuss the ways in which datasets can be interrogated and reviewed with an ethnographic perspective. They propose we conduct analyses which complement datamining—in which the data are taken as given and interpreted with a view to summarization—but focus on an exploratory practice of data investigation with a view to finding out the meaning behind the data, for example, the intent behind the actions that are rendered into behavioral logs. They call this practice “ethnomining”. This concept so beautifully described one aspect of the work I’d been doing around the time the authors were proposing this approach, that I wantonly used the term to intrigue and invite my data science and engineering colleagues to join with me in analysis of data from a dating site (Yahoo! Personals, which was a popular site at the time). The work we did then complemented work with Elizabeth Goodman, which had been more traditionally ethnographic with interviews, observations, site analyses, and which was presented and published in an EPIC2008 paper. […]

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