A Semi-Automated Approach to the Content Analysis of Experience Narratives - Modeling Users' Experiences with Interactive Systems - page 121

3

Understandability
Learnability

2

Efficiency

Novelty

Pragmatic Quality

Stimulation
Aesthetics in Interaction

Simplicity

Classic aesthetics

1

HQ-Stimulation

Fits context
Long-term usability

Visual Aesthetics

Relevant Others

0

Familiar

Effectiveness Self-expression

Missing functionality
Usefulness

Sense of community

-1

Capturing momentary information

Alleviate boredom in idle periods

Expressive aesthetics Fast access to information

Adaptable -2

HQ-Identification

-3

-4 -3 -2 -1 0 1 2 3 4

Dimension 1

Fig. 6.1 Multi-Dimensional Scaling on concept dissimilarity (eq. 6.7). Concepts connected
through lines belong to the same cluster. A-priori defined concepts are depicted in italics,
while superordinate concepts are denoted in bold.

tives in the interpretation process. They argued that the very same comparison that
can be performed on two objects (e.g. two flowers) resulting in the identification of
the objects' properties (e.g. size, shape, color), may also be performed on theoreti-
cal concepts. For instance, the flip-flop technique involves a systematic comparison
between a concept and its extreme opposite in identifying the concept's properties,
e.g. what is meant by “immediate” access to information: time, effort or ubiquity.
Strauss and Corbin (1998) emphasize the role of diversity in the cases in the
process of deriving new interpretations. This process may be supported through
the use of interactive visualizations. For instance, figure 6.2 illustrates an interac-
tive scatter plot that aims at enabling the researcher in browsing through diverse
narratives. It computes the similarity between narratives from the co-occurrence of
concepts (i.e. equation 6.6) and visualizes the first two dimensions derived from
Multi-Dimensional Scaling. As more narratives are analyzed, the plot is updated.
By selecting one of the points in the plot, the narrative is displayed on the right
part of the interface and the coded data are highlighted and annotated by the re-
spective concept. The researcher is further able to visualize other aspects of the
experience narratives such as self-reported satisfaction for a given experience, day
of occurrence for the reported experience, as well as the number of codes within
each narrative.