期刊论文

Examining Topics and Sentiments of Chronic Disease Patients'Online Reviews—Case Study of"Sweet Homeland"

中文

数据分析与知识发现

2096-3467

2023

7

10

95-108

10.11925/infotech.2096-3467.2022.0891

本校为第一机构

[目的]为及时掌握慢性病患者在不同患病阶段的关注主题与情感类型,构建评论主题情感协同挖掘模型.[方法]在LDA主题模型的基础上融入情感信息与时间信息,提出动态主题情感混合模型dUTSU.基于糖尿病患者评论数据,从主题识别效果、情感分类准确率验证模型有效性,开展主题-情感词分析和主题情感演化分析实现糖尿病患者不同患病阶段评论主题与情感协同挖掘.[结果]dUTSU的困惑度、主题平均相似度、情感分类准确率均优于JST、ASUM、UTSU等同类模型;利用dUTSU分析糖尿病患者评论数据,共识别出15个主题,得到疾病确诊阶段、并发症阶段等共7个时间片内的热点主题与伴生的情感强度及类型,揭示了主题情感随时...

[Objective]This paper constructs a model for topic-sentiment collaborative mining,aiming to understand chronic disease patients at different stages better.[Methods]First,we added sentiment and time features to the LDA model to create the new dUTSU(dynamic unsupervised topic and sentiment unification)model.Then,we retrieved posts by diabetes patients from an online health community.Finally,we assessed the dUTSU model's performance with the topic-sentiment analysis and the topic-sentiment evolution analysis.[Results]The dUTSU model had better perplexity,average topic similarity,and sentiment cla...