  Computer users are generally faced with difficulties in making correct
security decisions. While an increasingly fewer number of people are trying or
willing to take formal security training, online sources including news,
security blogs, and websites are continuously making security knowledge more
accessible. Analysis of cybersecurity texts can provide insights into the
trending topics and identify current security issues as well as how cyber
attacks evolve over time. These in turn can support researchers and
practitioners in predicting and preparing for these attacks. Comparing
different sources may facilitate the learning process for normal users by
persisting the security knowledge gained from different cybersecurity context.
Prior studies neither systematically analysed the wide-range of digital sources
nor provided any standardisation in analysing the trending topics from recent
security texts. Although LDA has been widely adopted in topic generation, its
generated topics cannot cover the cybersecurity concepts completely and
considerably overlap. To address this issue, we propose a semi-automated
classification method to generate comprehensive security categories instead of
LDA-generated topics. We further compare the identified 16 security categories
across different sources based on their popularity and impact. We have revealed
several surprising findings. (1) The impact reflected from cyber-security texts
strongly correlates with the monetary loss caused by cybercrimes. (2) For most
categories, security blogs share the largest popularity and largest
absolute/relative impact over time. (3) Websites deliver security information
without caring about timeliness much, where one third of the articles do not
specify the date and the rest have a time lag in posting emerging security
issues.
