Negative comment recognition model based on lightGBM

TianLin Zhang; ShuJie Li; XiaoRui Jing; JiaPeng Song; LuGe Shi; Xu He

doi:10.1117/12.2672779

28 March 2023 Negative comment recognition model based on lightGBM

TianLin Zhang, ShuJie Li, XiaoRui Jing, JiaPeng Song, LuGe Shi, Xu He

Proceedings Volume 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022); 125973Z (2023) https://doi.org/10.1117/12.2672779
Event: Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 2022, Nanjing, China

Abstract

With the popularization and rapid development of the internet, the negative impact caused by negative comments is exacerbated. The increasingly common negative comments on various video websites and social networking sites have exercised a malign influence on public opinion and caused adverse social consequences. This paper uses LightGBM to establish a high-performance negative comment prediction model. The data set selected in this paper is from the Internet movie database IMDB, in which positive and negative comments have been marked for our training model. After Bag of Words processing and TF-IDF processing of the dataset and substituting it into our training model, the researchers obtained the final model with an accuracy of more than 95%, which has a more satisfactory performance compared with the classical integrated model and the traditional binary classification model. Thus, it can be seen that this model has an advantage in identifying spiteful comments online.

Citation Download Citation

TianLin Zhang, ShuJie Li, XiaoRui Jing, JiaPeng Song, LuGe Shi, and Xu He "Negative comment recognition model based on lightGBM", Proc. SPIE 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 125973Z (28 March 2023); https://doi.org/10.1117/12.2672779

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KEYWORDS

Data modeling

Education and training

Internet

Detection and tracking algorithms

Feature extraction

Databases

Binary data

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