the same so we could see how each factor affects the total number of reviews.
The gray bands around the plotted lines
are bootstrap confidence intervals for
We generated a nomogram (see Figure 3) to visualize the results of our regression model,
10 helping us examine
the effect of each factor while controlling for other factors. The nomogram
consists of a series of scales. The Linear Predictor scale is the total number
of reviews in log scale. To calculate the
total number of reviews, we can draw a
straight line from the value of the “
total points” scale to the linear predictor
scale. The total points are calculated
by summing the points of each of the
scales of the three factors: releases,
downloads, and categories. To calculate the points value of each factor, we
can draw a line from the value in the
factor scale to the points scale. The
value in the points scale becomes the
points for that factor. For example, releases = 2, downloads = 100,000, and
categories = tools. We found that 2-re-
leases corresponded to approximately
seven points, 100,000-downloads corresponded to approximately 20 points,
and the tools category corresponded to
approximately five points. The sum was
32 total points, which corresponded to
approximately 2. 5 log scale, or 316 total
We found that as the number of
downloads and releases increased, the
total number of reviews also increased.
We found no relation between individual categories (such as communications, social, tools, and review count)
when we controlled for number of
downloads and releases. In contrast,
Pagano and Maalej20 and Hoon et al.
observed a relation between categories
and number of received reviews in the
Apple App Store; however, neither study
controlled for the other metrics in its
analysis. Those studies observed a relation between categories and number of
reviews that may be due to the interaction between categories and number of
downloads or between categories and
number of releases.
Spike in reviews following a release.
Finally, concerning the spike in reviews
following a release of an app in Google
Finding 4. Both the Google Play store
and the Apple App Store showed evi-
Figure 3. A nomograph of the effect of new releases, app category, and number of downloads
on total number of reviews received.
0 10 20 30 40 50 60 70 80 90 100
0 2 4 6 8 10 12 14 16 18 20
10,000 100,000 500,000 1,000,000 5,000,000 50,000,000100,000,000
0 20 40 60 80 100 120 140 160
Figure 4. Standard deviation of new reviews every 24 hours before and after the first
collected release for each studied app; each boxplot represents the standard deviation
from the median number of reviews for each app at that time.
96 − 72 − 48 − 24 0 24 48 72
Figure 2. Plots of the total number of reviews (logged) on the y-axis and three separate
graphs of app categories, number of downloads, and number of releases on the x-axis;
the graphs reflect the relation between the three factors and the total number of reviews.
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