国家自然科学基金项目（71173194, 71571162, 71772164）；国家社科基金应急管理体系建设研究专项项目（20VYJ073）；国家社科基金重大项目（17ZDA088）；浙江省自然基金一般项目（LY18D010006）。
Zhejiang University of Technology
National Natural Science Foundation of China (71173194, 71571162, 71772164); National Social Science Fund Emergency Management System construction special project (20VYJ073); National Social Science Fund Major Project (17ZDA088); Zhejiang Natural Fund General Project (LY18D010006).
With the continuous development of information technology in recent years, social network has become the main platform for its users to communicate ad express their own opinions. Characterized by rapid spread speed and great influence, even there may be resonance or mutual exclusion between public opinion information on different topics, social network information plays a negative influence on social stability and network security. In accordance with this situation, this study proposes a problem about the spread and control of MTBC public opinion based on multiple topics and budget constraints. Firstly, a set of nodes was found so that negative public opinion information can be effectively controlled and prevented at low cost. Secondly, an IGA approximate greedy algorithm with an approximate ratio of 1-√e was proposed, and an IGEA extended algorithm was raised for large social network data set. Rapid update and objective function calculation were achieved by using tree structured database. Finally, a numerical example was realized by employing real social network data set. The result showed that the algorithm proposed in this paper has higher efficiency and accuracy than the existing algorithm used to control the spread of public opinion information. And IGEA algorithm is suitable for large-scale social network data sets.