ArticleDrug safety2016
Social Media Listening for Routine Post-Marketing Safety Surveillance.
Article in Drug safety, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
39 citing papers in PubMed.
- Using Social Media Listening to Understand the Pressure Injury Experience: A Qualitative Descriptive Study.JMIR nursing · 2026Article
- Comparative Analysis of Potential Side Effects of Targeted Oral Hypoglycemic Agents Using Spontaneous Adverse Event Reports and Social Media Data.Pharmacoepidemiology and drug safety · 2026Article
- Social media data and its potential for pharmacovigilance: a comparative analysis of reported prevalences regarding drug-induced gingival overgrowth (DIGO).Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Opinion Mining of Erowid's Experience Reports on LSD and Psilocybin-Containing Mushrooms.Drug safety · 2025Article
- Social Listening for Patient Experiences With Stopping Extended-Release Buprenorphine: Content Analysis of Reddit Messages.Journal of medical Internet research · 2025Article
- Social listening applied to tailor communication on immunization in the Republic of Moldova.European journal of public health · 2025Article
- A Review of the Applications, Benefits, and Challenges of Generative AI for Sustainable Toxicology.Current research in toxicology · 2025Review
- Pharmacovigilance in the digital age: gaining insight from social media data.Experimental biology and medicine (Maywood, N.J.) · 2025Review
- Using Social Media as a Source of Real-World Data for Pharmaceutical Drug Development and Regulatory Decision Making.Drug safety · 2024Article
- Social Media Listening and Digital Profiling Study of People With Headache and Migraine: Retrospective Infodemiology Study.Journal of medical Internet research · 2023Article
- An industry perspective on the use of machine learning in drug and vaccine safety.Frontiers in drug safety and regulation · 2023Article
- A New Method to Extract Health-Related Quality of Life Data From Social Media Testimonies: Algorithm Development and Validation.Journal of medical Internet research · 2022Article
- [Utilizing social media data in post-market safety surveillance].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2021Article
- Combining Social Media and FDA Adverse Event Reporting System to Detect Adverse Drug Reactions.Drug safety · 2020Article
- Machine Learning Classifiers for Twitter Surveillance of Vaping: Comparative Machine Learning Study.Journal of medical Internet research · 2020Article
- Prospective Evaluation of Adverse Event Recognition Systems in Twitter: Results from the Web-RADR Project.Drug safety · 2020Article
- Drug Safety Issues Covered by Lay Media: A Cohort Study of Direct Healthcare Provider Communications Sent between 2001 and 2015 in The Netherlands.Drug safety · 2020Article
- Adverse Events in Twitter-Development of a Benchmark Reference Dataset: Results from IMI WEB-RADR.Drug safety · 2020Article
- Recommendations for the Use of Social Media in Pharmacovigilance: Lessons from IMI WEB-RADR.Drug safety · 2019Article
- Social Media Surveillance of Multiple Sclerosis Medications Used During Pregnancy and Breastfeeding: Content Analysis.Journal of medical Internet research · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionPost-marketing safety surveillance primarily relies on data from spontaneous adverse event reports, medical literature, and observational databases. Limitations of these data sources include potential under-reporting, lack of geographic diversity, and time lag between event occurrence and discovery. There is growing interest in exploring the use of social media ('social listening') to supplement established approaches for pharmacovigilance. Although social listening is commonly used for commercial purposes, there are only anecdotal reports of its use in pharmacovigilance. Health information posted online by patients is often publicly available, representing an untapped source of post-marketing safety data that could supplement data from existing sources.
objectivesThe objective of this paper is to describe one methodology that could help unlock the potential of social media for safety surveillance.
methodsA third-party vendor acquired 24 months of publicly available Facebook and Twitter data, then processed the data by standardizing drug names and vernacular symptoms, removing duplicates and noise, masking personally identifiable information, and adding supplemental data to facilitate the review process. The resulting dataset was analyzed for safety and benefit information.
resultsIn Twitter, a total of 6,441,679 Medical Dictionary for Regulatory Activities (MedDRA(®)) Preferred Terms (PTs) representing 702 individual PTs were discussed in the same post as a drug compared with 15,650,108 total PTs representing 946 individual PTs in Facebook. Further analysis revealed that 26 % of posts also contained benefit information.
conclusionSocial media listening is an important tool to augment post-marketing safety surveillance. Much work remains to determine best practices for using this rapidly evolving data source.
Indexed as
Identifiers
26798054What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.