Mining Potential Effects of HUMIRA in Twitter Posts Through Relational Similarity

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Article investigating HUMIRA effects mentioned in Twitter posts using a relational similarity-based method. The authors were able to identify effects previously known as well as potentially unreported, which demonstrates the power of this method and its potential for studying effects of other medications shared by Twitter users.

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5 p.

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Feng, Shichao; Jiang, Keyuan; Huang, Liyuan; Chen, Tingyu & Bernard, Gordon R. June 16, 2020.

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This article is part of the collection entitled: UNT Scholarly Works and was provided by the UNT College of Engineering to the UNT Digital Library, a digital repository hosted by the UNT Libraries. More information about this article can be viewed below.

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  • IOS Press
    Publisher Info: in association with the European Federation for Medical Informatics (EFMI)

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UNT College of Engineering

The UNT College of Engineering strives to educate and train engineers and technologists who have the vision to recognize and solve the problems of society. The college comprises six degree-granting departments of instruction and research.

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Article investigating HUMIRA effects mentioned in Twitter posts using a relational similarity-based method. The authors were able to identify effects previously known as well as potentially unreported, which demonstrates the power of this method and its potential for studying effects of other medications shared by Twitter users.

Physical Description

5 p.

Notes

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.

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  • Digital Personalized Health and Medicine, 270, IOS Press, June 16, 2020, pp. 1-5

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  • Publication Title: Digital Personalized Health and Medicine
  • Volume: 270
  • Page Start: 874
  • Page End: 878
  • Peer Reviewed: Yes

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UNT Scholarly Works

Materials from the UNT community's research, creative, and scholarly activities and UNT's Open Access Repository. Access to some items in this collection may be restricted.

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  • June 16, 2020

Added to The UNT Digital Library

  • May 27, 2022, 5:52 a.m.

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  • Nov. 28, 2023, 10:34 a.m.

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Feng, Shichao; Jiang, Keyuan; Huang, Liyuan; Chen, Tingyu & Bernard, Gordon R. Mining Potential Effects of HUMIRA in Twitter Posts Through Relational Similarity, article, June 16, 2020; (https://digital.library.unt.edu/ark:/67531/metadc1934099/: accessed July 14, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT College of Engineering.

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