ArticleInternational journal of environmental research and public health2020
The Voice of Drug Consumers: Online Textual Review Analysis Using Structural Topic Model.
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 39 citations in OpenAlex.
- Online Pharmacy Adoption and Consumer Perception: A Systematic Review of Existing Literature.Cureus · 2025Review
- Improving topic modeling performance on social media through semantic relationships within biomedical terminology.PloS one · 2025Article
- Measuring the relationship between museum attributes and visitors: An application of topic model on museum online reviews.PloS one · 2024Article
- Consumers' Opinions towards Public Health Effects of Online Games: An Empirical Study Based on Social Media Comments in China.International journal of environmental research and public health · 2022Article
- Exploring the Factors Associated with Mental Health Attitude in China: A Structural Topic Modeling Approach.International journal of environmental research and public health · 2022Article
- What Topics Do Members of the Eating Disorder Online Community Discuss and Empathize with? An Application of Big Data Analytics.Healthcare (Basel, Switzerland) · 2022Article
- Topic modeling and sentiment analysis of Chinese people's attitudes toward volunteerism amid the COVID-19 pandemic.Frontiers in psychology · 2022Article
- Exploring public attitudes toward live-streaming fitness in China: A sentiment and content analysis of China's social media Weibo.Frontiers in public health · 2022Article
- Generating actionable insights from free-text care experience survey data using qualitative and computational text analysis: A study protocol.HRB open research · 2022Article
- Investigating Learner's Online Learning Behavioural Changes during the COVID-19 Pandemic.Proceedings of the Association for Information Science and Technology. Association for Information Science and Technology · 2021Article
- Diversity in Psychological Research Activities: Quantitative Approach With Topic Modeling.Frontiers in psychology · 2021Article
- Effect of Employee-Customer Interaction Quality on Customers' Prohibitive Voice Behaviors: Mediating Roles of Customer Trust and Identification.Frontiers in psychology · 2021Article
- Exploring sources of patient dissatisfaction in mobile health communication: A text analysis based on structural topic model.Digital healthArticle
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many web-based pharmaceutical e-commerce platforms allow consumers to post open-ended textual reviews based on their purchase experiences. Understanding the true voice of consumers by analyzing such a large amount of user-generated content is of great significance to pharmaceutical manufacturers and e-commerce websites. The aim of this paper is to automatically extract hidden topics from web-based drug reviews using the structural topic model (STM) to examine consumers' concerns when they buy drugs online. The STM is a probabilistic extension of Latent Dirichlet Allocation (LDA), which allows the consolidation of document-level covariates. This innovation allows us to capture consumer dissatisfaction along with their dynamics over time. We extract 12 topics, and five of them are negative topics representing consumer dissatisfaction, whose appearances in the negative reviews are substantially higher than those in the positive reviews. We also come to the conclusion that the prevalence of these five negative topics has not decreased over time. Furthermore, our results reveal that the prevalence of price-related topics has decreased significantly in positive reviews, which indicates that low-price strategies are becoming less attractive to customers. To the best of our knowledge, our work is the first study using STM to analyze the unstructured textual data of drug reviews, which enhances the understanding of the aspects of drug consumer concerns and contributes to the research of pharmaceutical e-commerce literature.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.