Beyond the Posts: Analyzing Breast Implant Illness Discourse With Natural Language Processing and Deep Learning
BII discourse on X peaked in 2019 characterized predominantly by negative sentiment and fear. The strong correlation between fear/negative-based posts and explantation rates suggests social media discourse significantly influences patient decisions regarding breast implant removal.
Authors
- Wesley P. Thayer (ORCID: https://orcid.org/0000-0001-8160-9552)
- Anthony E. Bishay (ORCID: https://orcid.org/0000-0002-6057-3770)
- Elizabeth L. Dale (ORCID: https://orcid.org/0000-0002-3644-1591)
- Michael J Boctor (ORCID: https://orcid.org/0000-0002-9268-8417)
- Lisandro Montorfano
- Jorys Martinez‐Jorge
- Lisa Tabor Connor (ORCID: https://orcid.org/0000-0002-9776-8328)
- Aparna Vijayasekaran (ORCID: https://orcid.org/0000-0001-6143-1849)
- Christin A. Harless
- Cole Holan (ORCID: https://orcid.org/0000-0002-8742-8290)
- Arman Fijany (ORCID: https://orcid.org/0000-0002-2556-3307)
- William C. Lineaweaver (ORCID: https://orcid.org/0000-0001-6887-8491)
- Ronnie Mubang
Institutions
- Vanderbilt University (US)
- Loma Linda University (US)
- Mayo Clinic in Arizona (US)
- Vanderbilt University Medical Center (US)
Publication Details
- Journal
- Aesthetic Surgery Journal
- Published
- 2025-04-02
- DOI
- https://doi.org/10.1093/asj/sjaf047
- Citations
- 4
- Primary Topic
- Social Media in Health Education
- Type
- article
- Field-Weighted Citation Impact
- 8.67