Article

Using Large Language Models for sentiment analysis of health-related social media data: empirical evaluation and practical tips

2024-03-20

Abstract excerpt

Health-related social media data generated by patients and the public provide valuable insights into patient experiences and opinions toward health issues such as vaccination and medical treatments. Using Natural Language Processing (NLP) methods to analyze such data, however, often requires high-quality annotations that are difficult to obtain. The recent emergence of Large Language Models (LLMs) such as the Gene...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 28afe147-bbb9-52fd-bbb5-da0fb4994bd8
DOI: 10.1101/2024.03.19.24304544

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Using Large Language Models for sentiment analysis of health-related social media data: empirical evaluation and practical tipsDOI 10.1101/2024.03.19.24304544Read

Open-source solution for evaluation and benchmarking of large language models for public healthSemantic proximity Read

Large Language Models at Population Scale: A Survey and Taxonomy of Public Health ApplicationsSemantic proximity Read

Using Social Media to Help Understand Long COVID Patient Reported Health Outcomes: A Natural Language Processing ApproachSemantic proximity Read

Large Language Models in Healthcare Current Development and Future DirectionsSemantic proximity Read

A Systematic Review on the Role of Sentiment Analysis in HealthcareSemantic proximity Read

Predicting Behavioral Determinants of Health from Clinical Text Using Transformer Models and BiLSTMSemantic proximity Read

A Systematic Review of Testing and Evaluation of Healthcare Applications of Large Language Models (LLMs)Semantic proximity Read

Large Language Models in Portuguese for Healthcare: A Systematic ReviewSemantic proximity Read

Extracting Social Determinants of Health from Electronic Health Records: Development and Comparison of Rule-Based and Large Language Model MethodsSemantic proximity Read

Improving the Robustness of Large Language Models in Extracting Social Determinants of HealthSemantic proximity Read

irAE-GPT: Leveraging large language models to identify immune-related adverse events in electronic health records and clinical trial datasetsSemantic proximity Read

Comparing natural language processing representations of disease sequences for prediction in the electronic healthcare recordSemantic proximity Read