Interpretable Sentiment Analysis and Text Segmentation for Chinese Language

被引：0
|
作者：
Hou, Zhenghao [1 ]
Kolonin, A. [2 ]
机构：
[1] Novosibirsk State Univ, Novosibirsk 630090, Russia
[2] Aigents, Novosibirsk, Russia
来源：
OPTICAL MEMORY AND NEURAL NETWORKS | 2024年 / 33卷 / SUPPL3期
关键词：
social media; Chinese text; interpretable artificial intelligence; nature language processing; sentiment analysis;
D O I：
10.3103/S1060992X24700759
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
In this paper, we explored the performance of interpretable sentiment analysis models of different combinations for the Chinese text in social media. We made experiment to study how performance varies with the change of combination of different segmentation strategies and dictionary of words or n-grams. We found that with some good combination of segmentation strategies and dictionary of words or n-grams, the result can be improved and overtake the performance of ordinary sentiment analysis model of Chinese language. This way we show the importance of selection of segmentation strategies and dictionary for the sentiment analysis of Chinese text.
引用
收藏
页码：S483 / S489
页数：7
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