AUTHOR=Jiang Hao , Yin Xuehong 

TITLE=Association between community psychological label and user portrait model based on multimodal neural network

JOURNAL=Frontiers in Psychology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2022.918274

DOI=10.3389/fpsyg.2022.918274

ISSN=1664-1078

ABSTRACT=By analyzing traditional deep learning multi-mode retrieval methods, an optimized multi-mode retrieval model based on convolutional neural network is established. This paper proposes an innovative semi-supervised social network user portrait analysis model (UPAM) based on user portrait model, which integrates users' social information and some known user attribute information (such as educational background, residence, etc.) into a unified topic model framework. Finally, a semi-supervised user portrait analysis method based on user social information and partial known user attribute information is proposed. According to the correlation of user attributes, the cross-validation method is used to train model prediction task and improve the prediction effect. In the first level model, using different model to extract the features in the user query, the basis of the second hierarchy model, Stacking is used to further integration characteristics, finally realizes the attribute population forecast, through experimental verification show that the proposed model effectiveness in various attributes of a population.