Japanese anthropologist Jiro Kawakita devised the KJ method (on which affinity diagramming is based on) as a tool for use in anthropology to synthesize idiosyncratic observations of raw data obtained through fieldwork to find new hypotheses. We close by discussing what we have learnt by adapting affinity diagramming to our own practices, followed by conclusions.Ģ.1 Affinity Diagramming and the KJ MethodĪffinity diagramming is a technique used to externalize, make sense of, and organize large amounts of unstructured, far-ranging, and seemingly dissimilar qualitative data. We then take real-life examples from eight industrial research projects to illustrate the four stages of our particular use of affinity diagramming for interactive prototype evaluations. We begin by discussing related work on affinity diagrams, how they are used in HCI and interaction design, and existing support tools. The main contributions of this paper include: a systematic analysis of affinity diagramming use for prototype evaluations in HCI and interaction design over an extended period an adaptation of earlier affinity diagramming techniques such as the ones described by Beyer and Holtzblatt which have been tailored to suit small to medium projects and a discussion on practices that are relevant for general affinity diagramming. Finally, in documentation, we pick relevant user quotes and count notes to communicate and quantify our main findings.
We also discuss practices related to pruning the wall, which include merging, arranging, and removing note clusters. Third, in walking the wall, we take advantage of color-coded sticky notes (i.e., one color per participant) to check at a glance whether enough people have raised an issue. We also avoid using interview questions to structure the data, letting overarching topics naturally emerge from it. Second, when clustering notes, we invite team members to go through each other’s notes in sequence, to avoid ownership issues and to create a better understanding of the context when an observation of use is made. First, when creating notes, we embrace the affordances of paper and build affinity diagrams with physical paper by producing handwritten sticky notes. To better suit small to medium interaction design projects in industrial and academic contexts, we have tailored and scaled down Beyer and Holtzblatt’s six stages of contextual design to four stages. Our affinity teams usually consist of two researchers who collect data from 10 to 24 participants (i.e., observations of use during a task, and semi-structured interviews), independently write affinity notes (i.e., 500 to 2500 notes), and jointly analyze the data (i.e., build an affinity diagram) over a period of two to three weeks. In this paper, we reflect on a decade’s experience using affinity diagramming to evaluate interactive prototypes.
Common uses of affinity diagramming include analyzing contextual inquiry data clustering user attributes into profiles or requirements, problem framing and idea generation and prioritizing issues in usability tests. Affinity diagramming is a technique used to externalize, make sense of, and organize large amounts of unstructured, far-ranging, and seemingly dissimilar qualitative data.
First introduced in the 1960s, affinity diagramming (or the KJ method) has its origins in anthropology and social science and has widely been accepted within HCI research. Most of these studies have looked into methods that were originally conceived within and are closely related to design practice, such as probes, workbooks, and mood boards. Researchers have recently been looking into and studying different (design) methods and reflecting on how they are used in practice by the human-computer interaction (HCI) and interaction design communities.
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