Tracking the Spread of Pollen on Social Media Using Pollen-Related Messages From Twitter: Retrospective Analysis

Area of Science:

• Environmental Health
• Public Health
• Social Media Analytics

Background:

• Allergy disorders, driven by airborne allergens like pollen, are a growing global health concern, projected to affect 50% of Europeans within 15 years.
• Urbanization, industrialization, pollution, and climate change are exacerbating allergy prevalence.
• Pollen allergy represents a significant and increasing burden on public health systems worldwide.

Purpose of the Study:

• To analyze the spread of pollen symptom information on Twitter from December 2006 to January 2022.
• To evaluate public comments and trends to understand the impact of pollen on sensitive individuals.
• To enhance public health awareness regarding pollen-related issues.

Main Methods:

• Utilized large language models, dimensionality reduction, and unsupervised clustering for Twitter data analysis.
• Employed term frequency-inverse document frequency (TF-IDF) to identify key themes.
• Visualized findings using word clouds and semantic interaction graphs to uncover patterns in discussions about respiratory allergies.

Main Results:

• Highest message volumes occurred between March and August.
• A notable increase in patient-related tweets and reported symptoms, particularly in the morning, was observed in later years.
• Pollen allergy symptoms are experienced at a localized level, necessitating tailored public health responses.

Conclusions:

• Analyzing Twitter data provides valuable insights for preventive measures against pollen allergy.
• Social media interpretation can help mitigate the impact of pollen allergy on sensitive individuals.
• Leveraging online discourse can improve health information access and promote health equity.