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As an example, consider gem and jewel. These two
words tend to show up in similar contexts, and are
usually substitutable for one another. As such, even
though they do not frequently co-occur, they will be
judged very similar by the cosine metric.
Since the cosine is a measure of relatedness, for any
particular autoflight term, we can take the sum of
cosines across the other autoflight terms as a measure
of the centrality of the term. It turns out that the terms
that increase in salience across the interview sets (as
measured by relative frequency) also increase in
centrality.
Plot of variables on axis 1 and axis 2 / Stress : 0.2079
managed
selected
mode
guidance
thrust
speed
pitch
constraint restriction
computer
box
vertical
lateral
open
descent
climb
idle
fma
autothrust
select
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1
-- axis 1 -->
-- axis 2 -->
Plot of variables on axis 1 and axis 2 / Stress : 0.1910
managed
selected
mode
guidance
path
thrust
speed
pitch
restriction
computer
box
vertical
lateral
open
descent
climb
idle
fma
autothrust
select
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
-0.4 -0.2 0 0.2 0.4 0.6 0.8
-- axis 1 -->
-- axis 2 -->
Figure 1. Initial Interview (Init) Figure 2. First Line Interview (1L)
Plot of variables on axis 1 and axis 2 / Stress : 0 .1842
managed
sele cted
mode
g uidan ce
p ath
thrust
speed
pitch
t arget
constra in t
restriction
computer
box
vertical
la teral
open
descent clim b idle
fma
autothrust
select
-1.2
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
-1.5 -1 -0 .5 0 0.5 1
-- axis 1 -->
-- axis 2 -->
Plot of variables on axis 1 and axis 2 / Stress : 0.1619
select
fma autothrust
idle
climb
descent
open
lateral
vertical
box
computer
restriction
constraint
target
pitch
speed
thrust
path
guidance
mode
selected
managed
-1.2
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
-0.6 -0.4 -0.2 0 0.2 0.4 0.6
-- axis 1 -->
-- axis 2 -->
Figure 3. Second Line Interview (2L) Figure 4. Third Line Interview (3L)
Finally, we plot the terms in 2-dimensional space
using a multidimensional scaling algorithm. Figures 1
through 4 combine these measures in a single display.
Each figure represents one of the interview corpora.
The terms are arranged such that the distances among
terms reflect their similarities. The colors of the
terms indicate their centrality as measured by sum of
cosines measure for the third line interview. Warm
colors indicate central terms, while cool colors
indicate peripheral terms. We chose to use the
centrality measure from the third line interview so
that it would be easy to identify terms that are
outliers in early interview data but will become
central later. The font size of the term indicates the
salience of the term (as measured by relative
frequency in each interview set). The four composite
representations in order show the emergence of an
understanding of the conceptual relations of the
autoflight terms.
Term co-occurrence results Notice the shift in color
distribution across the figures. Terms that will be
central in 3L (depicted in red font, e.g., speed,
descent, managed) are spread about in the plot for the
initial interview, while terms that will be peripheral
in 3L (e.g., computer and pitch) are central in that
plot. Coding centrality this way makes shifts in
conceptual salience visually apparent.
Between the initial interview and the first line
interview, speed has become the highest frequency
term and is also the most central. Once pilots start
flying the A320, they quickly discover that speed
demands their attention. The simplest mode for
climbs in the A320 is called open climb, and the
terms open and climb, while not central, are located
close together in 1L. In the first line interview,
thrust, path and idle which will eventually be
essential parts of the model are still far from central.
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