Using a novel Naive Bayes algorithm for comparing centrality scores, we were able to predict the Corona Crisis' effects on small businesses more accurately.

Abstract

Aim: The aim of this research is to Predict the Concussion of  Corona Crisis over Small Businesses using Novel Naive Bayes Algorithm Comparing Centrality Score Algorithm. Materials and Methods: NovelNaive Bayes Algorithm with sample size = 110 and Centrality Score Algorithm with sample size = 110 with G power (value =0.6) were evaluated many times to predict the efficiency percentage. Results: Novel Naive Bayes algorithm has better accuracy (73.85%) when compared to Centrality Score algorithm accuracy (62.50%). The results achieved with significance value p=0.618 (p>0.05) shows that two groups are statistically insignificant. Conclusion: NovelNaive Bayes performed significantly better than the Centrality Score algorithm.