Emotion Prediction and Analysis of Weibo Users Combined with Portraits

Take the Granddaughter of the Confirmed Case in Chengdu as an Example

DOI

10.2991/978-94-6463-038-1_27How to use a DOI?

Keywords

Public opinion; Weibo; BERT; LightGBM; User portrait

Abstract

Since the outbreak of the novel coronavirus, Weibo has become one of the important platforms for Chinese netizens to receive information related to the epidemic. Behind the complexity of the news, netizens' emotions often affect the general social atmosphere, and the rapid spread of extreme negative emotions is not conducive to social harmony and stability. Therefore, it is particularly important to predict the emotional tendency of netizens and to pay attention to and guide users with negative tendencies. To improve the accuracy, reduce the amount of calculation and improve the running speed, this paper proposes a prediction process based on the BERT + LightGBM model. By taking advantage of the respective advantages of the two models and combining the emotional data of microblog content and user characteristics, this paper realizes the emotion analysis and prediction of Weibo users. The validity of the BERT + LightGBM model was verified by the case of the “granddaughter of a confirmed case in Chengdu”. Compared with BERT, LSTM, and CNN, the BERT + LightGBM composite model has higher accuracy and better application prospects.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ruixin Li
AU  - Jianhua Dai
PY  - 2022
DA  - 2022/12/15
TI  - Emotion Prediction and Analysis of Weibo Users Combined with Portraits
BT  - Proceedings of the 2022 3rd International Conference on Management Science and Engineering Management (ICMSEM 2022)
PB  - Atlantis Press
SP  - 292
EP  - 300
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-038-1_27
DO  - 10.2991/978-94-6463-038-1_27
ID  - Li2022
ER  -