A Novel Approach for Bots Detection in Sina Microblog

作者：Yang, Wu^*; Dong, Guozhong; Wang, Wei; Hu, Yaxue; Shen, Guowei; Yu, Miao

来源：Journal of Computational and Theoretical Nanoscience, 2015, 12(7): 1420-1425.

DOI：10.1166/jctn.2015.3907

• Sina Microblog
• Bots Detection
• Interaction-Based Feature
• Neural Network

Along with the widely using of microblog, third party services such as follower markets sell bots to customers to build fake influence and reputation. However, the bots and the customers that have large numbers of followers usually post spam messages such as promoted messages, messages containing malicious links. Our work is the first to do the in-depth analysis of different types of bots and study on detecting bots in follower markets in Sina microblog. In this paper, we propose an effective approach for bots detection based on interaction graph model and BP neural network. Based on empirical analysis of collected dataset, we build an interaction graph model based on user interaction and design robust interaction-based features. We conduct a comprehensive set of experiments to evaluate the proposed features using different machine learning classifiers. The results of our evaluation experiments show that BP neural network classifier using our proposed features is more effective to detect bots compared to other existing state-of-the-art approaches.

• 出版日期2015-7
• 单位哈尔滨工程大学