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. 2024 Oct 21:26:e58309.
doi: 10.2196/58309.

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

Martín Pérez-Pérez  1   2   3 , María Fernandez Gonzalez  4 , Francisco Javier Rodriguez-Rajo  4 , Florentino Fdez-Riverola  1   2   3
Affiliations

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

Martín Pérez-Pérez et al. J Med Internet Res. .

Abstract

Background: Allergy disorders caused by biological particles, such as the proteins in some airborne pollen grains, are currently considered one of the most common chronic diseases, and European Academy of Allergy and Clinical Immunology forecasts indicate that within 15 years 50% of Europeans will have some kind of allergy as a consequence of urbanization, industrialization, pollution, and climate change.

Objective: The aim of this study was to monitor and analyze the dissemination of information about pollen symptoms from December 2006 to January 2022. By conducting a comprehensive evaluation of public comments and trends on Twitter, the research sought to provide valuable insights into the impact of pollen on sensitive individuals, ultimately enhancing our understanding of how pollen-related information spreads and its implications for public health awareness.

Methods: Using a blend of large language models, dimensionality reduction, unsupervised clustering, and term frequency-inverse document frequency, alongside visual representations such as word clouds and semantic interaction graphs, our study analyzed Twitter data to uncover insights on respiratory allergies. This concise methodology enabled the extraction of significant themes and patterns, offering a deep dive into public knowledge and discussions surrounding respiratory allergies on Twitter.

Results: The months between March and August had the highest volume of messages. The percentage of patient tweets appeared to increase notably during the later years, and there was also a potential increase in the prevalence of symptoms, mainly in the morning hours, indicating a potential rise in pollen allergies and related discussions on social media. While pollen allergy is a global issue, specific sociocultural, political, and economic contexts mean that patients experience symptomatology at a localized level, needing appropriate localized responses.

Conclusions: The interpretation of tweet information represents a valuable tool to take preventive measures to mitigate the impact of pollen allergy on sensitive patients to achieve equity in living conditions and enhance access to health information and services.

Keywords: LLM; Twitter; knowledge reconstruction; large language model; pollen; respiratory allergies; text mining.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Applied analysis workflow. The analysis began with collecting pollen-related tweets and user data, filtered for English content and curated for problem domain relevancy. KNN: k-nearest neighbor; LLM: large language model; PCA: principal component analysis; TF-IDF: term frequency–inverse document frequency.
Figure 2
Figure 2
Evolution of "pollen" discussions on Twitter from December 2006 to January 2022. The figure shows the annual percentage of tweets mentioning “declared patients” affected by pollen allergies, with a polynomial trend line indicating overall tendencies.
Figure 3
Figure 3
Evolution of the different topic clusters in the pollen-related discussions and their relevance from December 2006 to January 2022.
Figure 4
Figure 4
Top comentioned hashtags in pollen-related discussions. Knowledge graph representing the comention hashtags from December 2006 to January 2022.
Figure 5
Figure 5
Top comentioned health-related topics identified in first-person messages. Knowledge graph representing the comentioned health-related topics identified from December 2006 to January 2022 in pollen-related discussions.
Figure 6
Figure 6
Evolution of Twitter conversations related to “pollen” within the recognized topic, based on Twitter messages containing at least one medical term, from December 2006 to January 2022.
Figure 7
Figure 7
Evolution of headache and migraine mentions on Twitter (top) and in pollen-related messages (bottom).
Figure 8
Figure 8
Top shared resources by the community. This figure shows the most shared URLs on Twitter grouped by topic using website embeddings for clustering.
See this image and copyright information in PMC

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