Inductive-Deductive Reasoning in Qualitative Analysis using ATLAS.ti: Trending Cybersecurity Twitter Data Analytics

With the advent of technologies and data created each day in new media, cybersecurity is the main concern for many researchers. One of the main questions is the trending data analytics on cybersecurity and the various approaches to make sense of qualitative data, especially using Twitter data analytics on cybersecurity. There are two main types of qualitative data reasoning: inductive and deductive. In this paper, four steps are engaged in demonstrating the application of inductive and deductive approaches using computer-aided qualitative data analysis software of ATLAS.ti. The first step involves Twitter data import into ATLAS.ti using different hashtag keywords such as #cybercrime, #computersecurity, #cybersecurity and #cyberattack. The second step involves reducing overlapping tweets, which have been imported from the first step. The third step highlights the inductive and deductive approaches in making sense and reasoning the Twitter data. The final step involves the output of the analysed data for reporting purposes. As a result, this study found an operational feature in ATLAS.ti that could facilitate inductive and deductive reasoning in qualitative data analytics. Not only is the process of carrying out such inductive and deductive reasoning easy, but the features in the software also facilitate the seamless output for reporting purposes. The study's implication is a demonstration of inductive and deductive reasoning in qualitative data analytics using ATLAS.ti, which could be employed by any future researcher who is involved in qualitative research and data analytics properly.