  Sentiment Analysis provides an opportunity to understand the subject(s),
especially in the digital age, due to an abundance of public data and effective
algorithms. Cybersecurity is a subject where opinions are plentiful and
differing in the public domain. This descriptive research analyzed
cybersecurity content on Twitter and Reddit to measure its sentiment, positive
or negative, or neutral. The data from Twitter and Reddit was amassed via
technology-specific APIs during a selected timeframe to create datasets, which
were then analyzed individually for their sentiment by VADER, an NLP (Natural
Language Processing) algorithm. A random sample of cybersecurity content (ten
tweets and posts) was also classified for sentiments by twenty human annotators
to evaluate the performance of VADER. Cybersecurity content on Twitter was at
least 48% positive, and Reddit was at least 26.5% positive. The positive or
neutral content far outweighed negative sentiments across both platforms. When
compared to human classification, which was considered the standard or source
of truth, VADER produced 60% accuracy for Twitter and 70% for Reddit in
assessing the sentiment; in other words, some agreement between algorithm and
human classifiers. Overall, the goal was to explore an uninhibited research
topic about cybersecurity sentiment
