Research Article
Detection Method of Abnormal Behavior of Network Public Opinion Data Based on Artificial Intelligence
@INPROCEEDINGS{10.1007/978-3-030-67871-5_30, author={Ying-jian Kang and Lei Ma and Yan-ning Zhang}, title={Detection Method of Abnormal Behavior of Network Public Opinion Data Based on Artificial Intelligence}, proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part I}, proceedings_a={ADHIP}, year={2021}, month={2}, keywords={Artificial intelligence Network public opinion Data abnormal behavior Detection method}, doi={10.1007/978-3-030-67871-5_30} }- Ying-jian Kang
Lei Ma
Yan-ning Zhang
Year: 2021
Detection Method of Abnormal Behavior of Network Public Opinion Data Based on Artificial Intelligence
ADHIP
Springer
DOI: 10.1007/978-3-030-67871-5_30
Abstract
In order to improve the effect of network public opinion data abnormal behavior detection, an artificial intelligence-based network public opinion data abnormal behavior detection method is proposed. By constructing the network public opinion data model, recognizing the evolution rule of network public opinion data, locating the abnormal data area according to the behavior detection algorithm, and using the probability neural network under artificial intelligence to detect the abnormal data behavior. The experimental results show that the detection method proposed this time is 28.12% and 84.37% higher than the two traditional methods when detecting large-scale public opinion abnormal behavior data. It can be seen that the detection method based on artificial intelligence is not restricted by the volume of network data, and the detection effect is better.
