Combining Topic Modeling, Sentiment Analysis, and Corpus Linguistics to Analyze Unstructured Web-Based Patient Experience Data: Case Study of Modafinil Experiences

This study demonstrated the value of combining NLP with linguistic techniques for analyzing large unstructured text datasets. Despite varying opinions, findings were methodologically consistent and challenged existing clinical evidence. This suggests that patient-generated data could potentially provide valuable insights into treatment outcomes, potentially improving clinical understanding and patient care.

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Publication Details

Journal
Journal of Medical Internet Research
Published
2024-12-11
DOI
https://doi.org/10.2196/54321
Citations
10
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
18.94
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article

Combining Topic Modeling, Sentiment Analysis, and Corpus Linguistics to Analyze Unstructured Web-Based Patient Experience Data: Case Study of Modafinil Experiences

Frances Griffiths, Julia Walsh, Jonathan Cave
10 citations
Journal of Medical Internet Research
Computational and Text Analysis Methods
18.94
article

Combining Topic Modeling, Sentiment Analysis, and Corpus Linguistics to Analyze Unstructured Web-Based Patient Experience Data: Case Study of Modafinil Experiences

Frances Griffiths, Julia Walsh, Jonathan Cave
article en
10 citations

Abstract

This study demonstrated the value of combining NLP with linguistic techniques for analyzing large unstructured text datasets. Despite varying opinions, findings were methodologically consistent and challenged existing clinical evidence. This suggests that patient-generated data could potentially provide valuable insights into treatment outcomes, potentially improving clinical understanding and patient care.

Journal of Medical Internet ResearchVol. 26
University of the Witwatersrand (ZA), University of Warwick (GB)
Openalex Percentile: Top 1%
Computational and Text Analysis Methods
18.94
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