Related Experiment Video
Updated: Sep 12, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Temporal Evolution of Public Health Sentiment: A Longitudinal Analysis
Samaneh Madanian1, Vahid Bakhtiari2, Vincent Feng1
1Department of Data Science and Artificial Intelligence, AUT, Auckland, New Zealand.
None:
This study advances our understanding of public health crisis communication by conducting a longitudinal analysis. As COVID-19 has been the largest public health crisis to date, we performed sentiment analysis on it. While previous research focused on discrete time periods, our study examines the arc of pandemic-related discourse from 2020 to 2022, revealing long-term patterns in public sentiment evolution. Using advanced natural language processing techniques and temporal pattern analysis, we identify key transition points in public health discourse and sentiment, offering insights for future crisis communication strategies.
More Related Videos
09:08Developing a Salivary Antibody Multiplex Immunoassay to Measure Human Exposure to Environmental Pathogens
Published on: September 12, 2016
06:55Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Related Concept Videos
Longitudinal Research
Longitudinal Studies
Steps in Outbreak Investigation
Introduction to Epidemiology
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time...
Causality in Epidemiology