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Especially on the Internet, popular topics in computer sciences which are artificial intelligence, big data, business analytics, data mining, data science, deep learning, and machine learning have been compared or classified using confusing Venn diagrams without any scientific proof. Relationships among the topics have been visualized in this study with the help of Venn diagrams to add scientificity to visualizations. Therefore, this study aims to determine the interactions among the seven popular topics in computer sciences. Five books for each topic (35 books) were included in the analysis. To illustrate the interactions among these topics, the Latent Dirichlet Allocation (LDA) analysis, a topic modeling analysis method, was applied. Further, the pairwise correlation was applied to determine the relationships among the chosen topics. The LDA analysis produced expected results in differentiating the topics, and pairwise correlation results revealed that all the topics are related to each other and that it is challenging to differentiate between them. [ABSTRACT FROM AUTHOR]