Stud Health Technol Inform. 2020 Jun 16;270:874-878. doi: 10.3233/SHTI200286.

Mining Potential Effects of HUMIRA in Twitter Posts Through Relational Similarity.

Studies in health technology and informatics

Keyuan Jiang, Shichao Feng, Liyuan Huang, Tingyu Chen, Gordon R Bernard

PMID: 32570507 DOI: 10.3233/SHTI200286

Abstract

HUMIRA, a biologic therapy, has been approved to treat autoimmune diseases and been marketed in many countries worldwide. Much like other medications, it demonstrates many effects on the human body. It is important to understand its effects from the information generated by its users, and social media is one of the venues its users share their experience with the medication. To understand what HUMIRA effects were reported on Twitter, we utilized a relational similarity-based approach to infer HUMIRA effects based upon known medication-effect relations of other medications. With a corpus of 3.6 million preprocessed, "clean" tweets, a total of 55 effects were identified, and among them, 46 were previously observed, and nine were potentially unreported after verification with six reliable sources. The results not only indicate that many HUMIRA effects shared by the Twitter users are consistent with those previously reported, but also demonstrate the power and utility of our method, making it applicable to studying effects of other medications shared by Twitter users.

Keywords: HUMIRA; medication effects; mining social media; relation extraction; relational similarity

Substances

• Adalimumab

MeSH terms

• Adalimumab
• Data Mining
• Humans
• Social Media*

Publication Types

• Journal Article