Leiden University Scholarly Publications

Dirkson, A.R.; Verberne, S.; Sarker, A.; Kraaij, W. (2019)

Data-Driven Lexical Normalization for Medical Social Media

Article / Letter to editor

In the medical domain, user-generated social media text is increasingly used as a valuable
complementary knowledge source to scientific medical literature. The extraction of this knowledge is
complicated by colloquial language use and misspellings. However, lexical normalization of such
data has not been addressed effectively. This paper presents a data-driven lexical normalization
pipeline with a novel spelling correction module for medical social media. Our method significantly
outperforms state-of-the-art spelling correction methods and can detect mistakes with an F₁ of 0.63
despite extreme imbalance in the data. We also present the first corpus for spelling mistake detection
and correction in a medical patient forum.

All authors

Dirkson, A.R.; Verberne, S.; Sarker, A.; Kraaij, W.

Date

2019-08-20

Journal

Multimodal Technologies and Interaction

Volume

3

Issue

3

Pages

60

DOI

doi:10.3390/mti3030060

Link

https://doi.org/10.3390/mti3030060