CoDA (Communities through Directed Affiliations) algorithm is a kind of community detection algorithm which based on probability model can successfully detects 2-mode communities.?The F-measure criterion, for information retrieval, was adapted to the evaluation of CoDA algorithm in directed networks with overlapping communities or non-overlapping communities . The value of F1-measure that in F-measure criterion can reflect whether CoDA algorithm performs well or not .The data sets used in the experiment was generated by the LFR Benchmark tool. The minimum number of nodes in data set was 100 and the maximum was 20000, and we did an evaluated experiment when every 100 nodes were added. The results show that CoDA algorithm performs well when the number of nodes is bellow 1600. However,once the number of nodes is above 1600, CoDA algorithm’s performance becomes worse with the increase of the number of nodes, that proves the CoDA algorithm which based on probability model is applicable to the community detection of small-scale networks .