Multilingual analysis of public discourse on opioid and non-opioid analgesics through social media: a cross-sectional infodemiological study

The global opioid crisis has intensified concerns regarding misuse, overdose-related mortality, and the associated social and economic burden of both prescribed and illicit opioids. Social media platforms provide large volumes of real-time data that enable the capture of public perceptions, emerging risks, and shifts in discourse. This study analyzes a decade of conversations on X to characterize temporal trends, identify thematic patterns, and compare the evolution of public discourse in English and Spanish on opioids and other analgesics. A cross-sectional analysis was conducted of all posts on X between 2014 and 2024 containing generic names of opioid analgesics, non-opioid analgesics, and opioid antagonists approved by national regulatory agencies. Following data collection, tweets were filtered by language and underwent normalization, cleaning, and lemmatization. Topic modeling was performed using Latent Dirichlet Allocation, applying online training with mini-batches to manage the size of the corpus. A total of 1,874,907 tweets were analyzed. Major opioids consistently generated the highest volume of discourse in both languages. Topic modeling revealed linguistic divergences: English-language tweets focused on personal experiences with opioids, the opioid crisis, and the pharmaceutical industry, whereas Spanish-language tweets emphasized therapeutic use, self-medication, alternatives for chronic pain, and emerging concerns regarding opioid potency. Analysis of X represents a sensitive and dynamic tool for monitoring public discourse on opioids and other analgesics. The findings reveal relevant linguistic and cultural differences in narratives surrounding these medications, as well as temporal patterns aligned with epidemiological, media, and regulatory changes. Continuous social media monitoring enables early detection of shifts in risk perception and public attention, providing key insights for health communication, the identification of emerging risks, and the design of interventions tailored to specific sociocultural contexts.

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Journal
BMC Medical Research Methodology
Published
2026-04-27
DOI
https://doi.org/10.1186/s12874-026-02850-z
Primary Topic
Opioid Use Disorder Treatment
Type
article
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article

Multilingual analysis of public discourse on opioid and non-opioid analgesics through social media: a cross-sectional infodemiological study

M. Álvarez-Mon, O. Fraile-Martínez, MA Ortega, J. Quintero et al.
BMC Medical Research Methodology
Opioid Use Disorder Treatment
article

Multilingual analysis of public discourse on opioid and non-opioid analgesics through social media: a cross-sectional infodemiological study

M. Álvarez-Mon, O. Fraile-Martínez, MA Ortega, J. Quintero, JP Chart-Pascual, A. Ruiz-Iniesta, MA Alvarez-Mon, I. Morales, J. Domingo-Espiñeira, C. García-Montero, T. Valades, F. Mora, R. Perez-Araluce
article en

Abstract

The global opioid crisis has intensified concerns regarding misuse, overdose-related mortality, and the associated social and economic burden of both prescribed and illicit opioids. Social media platforms provide large volumes of real-time data that enable the capture of public perceptions, emerging risks, and shifts in discourse. This study analyzes a decade of conversations on X to characterize temporal trends, identify thematic patterns, and compare the evolution of public discourse in English and Spanish on opioids and other analgesics. A cross-sectional analysis was conducted of all posts on X between 2014 and 2024 containing generic names of opioid analgesics, non-opioid analgesics, and opioid antagonists approved by national regulatory agencies. Following data collection, tweets were filtered by language and underwent normalization, cleaning, and lemmatization. Topic modeling was performed using Latent Dirichlet Allocation, applying online training with mini-batches to manage the size of the corpus. A total of 1,874,907 tweets were analyzed. Major opioids consistently generated the highest volume of discourse in both languages. Topic modeling revealed linguistic divergences: English-language tweets focused on personal experiences with opioids, the opioid crisis, and the pharmaceutical industry, whereas Spanish-language tweets emphasized therapeutic use, self-medication, alternatives for chronic pain, and emerging concerns regarding opioid potency. Analysis of X represents a sensitive and dynamic tool for monitoring public discourse on opioids and other analgesics. The findings reveal relevant linguistic and cultural differences in narratives surrounding these medications, as well as temporal patterns aligned with epidemiological, media, and regulatory changes. Continuous social media monitoring enables early detection of shifts in risk perception and public attention, providing key insights for health communication, the identification of emerging risks, and the design of interventions tailored to specific sociocultural contexts.

BMC Medical Research Methodology
Universidad Complutense de Madrid (ES), Universidad de La Rioja (ES), University of the Basque Country (ES), Universidad de Alcalá (ES), Instituto Cajal (ES), BioCruces Health research Institute (ES), Hospital Universitario de Torrejón (ES), Centro de Investigación Biomédica en Red de Salud Mental (ES), Hospital Universitario Príncipe de Asturias (ES), Universidad a Distancia de Madrid (ES), Hospital Universitario Araba (ES), Navarre Institute of Health Research (ES), Osakidetza (ES), Instituto Ramón y Cajal de Investigación Sanitaria (ES), Hospital Universitario Infanta Leonor (ES)
Quality Education
Openalex Percentile: Top 6%
Opioid Use Disorder Treatment
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