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A Multi-Stance Detection Method by Fusing Sentiment Features

التفاصيل البيبلوغرافية
العنوان: A Multi-Stance Detection Method by Fusing Sentiment Features
المؤلفون: Weidong Huang, Jinyuan Yang
المصدر: Applied Sciences, Vol 14, Iss 9, p 3916 (2024)
بيانات النشر: MDPI AG, 2024.
سنة النشر: 2024
المجموعة: LCC:Technology
LCC:Engineering (General). Civil engineering (General)
LCC:Biology (General)
LCC:Physics
LCC:Chemistry
مصطلحات موضوعية: stance detection, deep learning, LDA, sentiment lexicon, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
الوصف: Stance information has a significant influence on market strategy, government policy, and public opinion. Users differ not only in their polarity but also in the degree to which they take a stand. The traditional classification of stances is quite simple and cannot fully depict the diversity of stances. At the same time, traditional approaches ignore user sentiment features when expressing their stances. As a result, this paper develops a multi-stance detection model by fusing sentiment features. First, a five-category stance indicator system is built based on the LDA model, then sentiment features are extracted from the reviews using the sentiment lexicon, and finally, stance detection is implemented using a hybrid neural network model. The experiment shows that the proposed method can classify stances into five categories and perform stance detection more accurately.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2076-3417
Relation: https://www.mdpi.com/2076-3417/14/9/3916; https://doaj.org/toc/2076-3417
DOI: 10.3390/app14093916
URL الوصول: https://doaj.org/article/57ebab7385ae48dd929f1699ede2b5b4
رقم الانضمام: edsdoj.57ebab7385ae48dd929f1699ede2b5b4
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20763417
DOI:10.3390/app14093916