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Mingqi Tu,1,* Sangsang Xiong,1,* Shengxia Lv,2,* Xiaoting Wu,1 Hantong Hu,3 Renjie Hu,4 Jianqiao Fang,1 Xiaomei Shao1 1Key Laboratory for Research ofAcupuncture Treatment and Transformation of Emotional Diseases, Key Laboratory of Acupuncture and Neurology of Zhejiang Province, The Third Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, People’s Republic of China; 2The School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, People’s Republic of China; 3The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, People’s Republic of China; 4The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiaomei Shao, Key Laboratory for Research of Acupuncture Treatment and Transformation of Emotional Diseases, Key Laboratory of Acupuncture and Neurology of Zhejiang Province, The Third Clinical Medical College, Zhejiang Chinese Medical University, No. 548, Binwen Road, Binjiang District, Hangzhou, Zhejiang Province, People’s Republic of China, Tel +86 189 5713 0287, Email 13185097375@163.comIntroduction: Acupuncture has a long history of treating major depressive disorder (MDD), yet the acupoint selection of acupuncture for MDD varies greatly. This study aimed to explore the characteristics and principles of acupuncture for MDD by analyzing clinical trials of acupuncture for MDD using data mining techniques.Methods: In this study, clinical trials of acupuncture for MDD were retrieved and relevant data were extracted, and then the data were analyzed by data mining techniques. In addition, association rule mining, network analysis and hierarchical cluster analysis were used to determine the correlation between different acupoints.Results: The results revealed that GV20, LR3, PC6, SP6 and GV29 were used most frequently; acupoints in the Yang meridian were used