Comparing naive Bayes, decision trees, and SVM with AUC and accuracy

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Locate the Hate: Detecting Tweets against Blacks (2013, methodology): “We chose to implement the Naïve Bayes classifier, which performs just as well as more sophisticated classifiers (Huang et al. 2003), to distinguish between racist and nonracist tweets.”
An experimental comparison of performance measures for classification (2009, background): “For instance, it is said in (Huang et al., 2003) that Naive Bayes and pruned decision trees are very similar in predictive accuracy.”
Decision Tree and Naïve Bayes Algorithm for Classification and Generation of Actionable Knowledge for Direct Marketing (2013, methodology): “Each category consists of several algorithms, but the most popular from each category that are used extensively are C4.5, Naïve Bayes, K-Nearest Neighbors, and Backpropagation Neural Network [2,9,10].”