  In a previous study, we investigated the frequency distribution of the email
size in the system log data of the main email server for the staff on a campus
network. We found that the frequencies of email sizes followed a power-law
distribution and discovered two inflection points in the distribution. After
analyzing these results, we collected new system log data for both staff and
students for the period from April 1, 2009 to March 31, 2015 and analyzed the
frequency distributions per academic year. The results of the earlier
investigation were replicated for each of these distributions. Then, we
disaggregated the system log data for the staff for the period from May 1, 2015
to July 31, 2015 using the email header "Content-Type" and created four
subdistributions. Frequency distributions were calculated for the disaggregated
data. We then proposed and evaluated a model to explain the overall frequency
distribution as a sum of the four subdistributions. The correlation coefficient
between the observed frequency distribution and the distribution predicted by
our model was 0.8408 for the staff. This coefficient confirmed that our
approach can successfully model and predict the size distribution of emails.
